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  • 1.
    Andersson, Christoffer
    University of Skövde, School of Humanities and Informatics.
    PELICAN: a PipELIne, including a novel redundancy-eliminating algorithm, to Create and maintain a topicAl family-specific Non-redundant protein database2005Independent thesis Advanced level (degree of Master (One Year))Student thesis
    Abstract [en]

    The increasing number of biological databases today requires that users are able to search more efficiently among as well as in individual databases. One of the most widespread problems is redundancy, i.e. the problem of duplicated information in sets of data. This thesis aims at implementing an algorithm that distinguishes from other related attempts by using the genomic positions of sequences, instead of similarity based sequence comparisons, when making a sequence data set non-redundant. In an automatic updating procedure the algorithm drastically increases the possibility to update and to maintain the topicality of a non-redundant database. The procedure creates a biologically sound non-redundant data set with accuracy comparable to other algorithms focusing on making data sets non-redundant

  • 2.
    Benediktsson, Elís Ingi
    University of Skövde, School of Humanities and Informatics.
    Detection and analysis of megasatellites in the human genome using in silico methods2005Independent thesis Advanced level (degree of Master (One Year))Student thesis
    Abstract [en]

    Megasatellites are polymorphic tandem repetitive sequences with repeat-units longer than or equal to 1000 base pairs. The novel algorithm Megasatfinder predicts megasatellites in the human genome. A structured method of analysing the algorithm is developed and conducted. The analysis method consists of six test scenarios. Scripts are created, which execute the algorithm using various parameter settings. Three nucleotide sequences are applied; a real sequence extracted from the human genome and two random sequences, generated using different base probabilities. Usability and accuracy are investigated, providing the user with confidence in the algorithm and its output. The results indicate that Megasatfinder is an excellent tool for the detection of megasatellites and that the generated results are highly reliable. The results of the complete analysis suggest alterations in the default parameter settings, presented as user guidelines, and state that artificially generated sequences are not applicable as models for real DNA in computational simulations.

  • 3.
    Borgmästars, Emmy
    University of Skövde, School of Bioscience.
    Functional analysis of circulating microRNAs in pancreatic cancer2018Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
    The full text will be freely available from 2020-01-30 12:27
  • 4.
    Candelli, Tito
    University of Skövde, School of Life Sciences.
    NOVEL APPROACH TO STORAGE AND STORTING OF NEXT GENERATION SEQUENCING DATA FOR THE PURPOSE OF FUNCTIONAL ANNOTATION TRANSFER2012Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The problem of functional annotation of novel sequences has been a sigfinicant issue for many laboratories that decided to apply next generation sequencing techniques to less studied species. In particular experiments such as transcriptome analysis heavily suer from this problem due to the impossibility of ascribing their results in a relevant biological context. Several tools have been proposed to solve this problem through homology annotation transfer. The principle behind this strategy is that homologous genes share common functions in dierent organisms, and therefore annotations are transferable between these genes. Commonly, BLAST reports are used to identify a suitable homologousgene in a well annotated species and the annotation is then transferred fromthe homologue to the novel sequence. Not all homologues, however, possess valid functional annotations. The aim of this project was to devise an algorithm to process BLAST reports and provide a criterion to discriminate between homologues with a biologically informative and uninformative annotation, respectively. In addition, all data obtained from the BLAST report isto be stored in a relational database for ease of consultation and visualization. In order to test the solidity of the system, we utilized 750 novel sequences obtained through application of next generation sequencing techniques to Avena sativa samples. This species particularly suits our needs as it represents the typical target for homology annotation transfer: lack of a reference genome and diculty in attributing functional annotation. The system was able to perform all the required tasks. Comparisons between best hits asdetermined by BLAST and best hits as determined by the algorithm showed a significant increase in the biological significance of the results when thealgorithm sorting system was applied.

  • 5.
    Chaudhari, Aditi
    et al.
    Wallenberg Laboratory, Department of Molecular and Clinical Medicine, University of Gothenburg, Sweden.
    Krumlinde, Daniel
    Wallenberg Laboratory, Department of Molecular and Clinical Medicine, University of Gothenburg, Sweden / Scientific Solutions, Stockholm, Sweden.
    Lundqvist, Annika
    Wallenberg Laboratory, Department of Molecular and Clinical Medicine, University of Gothenburg, Sweden.
    Akyurek, Levent M
    Department of Medical Chemistry and Cell Biology, University of Gothenburg, Sweden.
    Bandaru, Sashidhar
    Department of Medical Chemistry and Cell Biology, University of Gothenburg, Sweden.
    Skalen, Kristina
    Wallenberg Laboratory, Department of Molecular and Clinical Medicine, University of Gothenburg, Sweden.
    Stahlman, Marcus
    Wallenberg Laboratory, Department of Molecular and Clinical Medicine, University of Gothenburg, Sweden.
    Boren, Jan
    Wallenberg Laboratory, Department of Molecular and Clinical Medicine, University of Gothenburg, Sweden.
    Wettergren, Yvonne
    Department of Surgery, University of Gothenburg, Sweden.
    Ejeskär, Katarina
    University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Health and Education. Department of Medical and Clinical Genetics, University of Gothenburg, Sweden.
    Sopasakis, Victoria Rotter
    Wallenberg Laboratory, Department of Molecular and Clinical Medicine, University of Gothenburg, Sweden.
    p110 alpha Hot Spot Mutations E545K and H1047R Exert Metabolic Reprogramming Independently of p110 alpha Kinase Activity2015In: Molecular and Cellular Biology, ISSN 0270-7306, Vol. 35, no 19, p. 3258-3273Article in journal (Refereed)
    Abstract [en]

    The phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K) catalytic subunit p110α is the most frequently mutated kinase in human cancer, and the hot spot mutations E542K, E545K, and H1047R are the most common mutations in p110α. Very little is known about the metabolic consequences of the hot spot mutations of p110α in vivo. In this study, we used adenoviral gene transfer in mice to investigate the effects of the E545K and H1047R mutations on hepatic and whole-body glucose metabolism. We show that hepatic expression of these hot spot mutations results in rapid hepatic steatosis, paradoxically accompanied by increased glucose tolerance, and marked glycogen accumulation. In contrast, wild-type p110α expression does not lead to hepatic accumulation of lipids or glycogen despite similar degrees of upregulated glycolysis and expression of lipogenic genes. The reprogrammed metabolism of the E545K and H1047R p110α mutants was surprisingly not dependent on altered p110α lipid kinase activity.

  • 6.
    Chawade, Aakash
    et al.
    Department of Cell and Molecular Biology, Göteborg University, Box 462, 403 20 Göteborg, Sweden.
    Bräutigam, Marcus
    Department of Cell and Molecular Biology, Göteborg University, Box 462, 403 20 Göteborg, Sweden.
    Lindlöf, Angelica
    University of Skövde, School of Humanities and Informatics.
    Olsson, Olof
    Department of Cell and Molecular Biology, Göteborg University, Box 462, 403 20 Göteborg, Sweden.
    Olsson, Björn
    University of Skövde, School of Humanities and Informatics.
    Putative cold acclimation pathways in Arabidopsis thaliana identified by a combined analysis of mRNA co-expression patterns, promoter motifs and transcription factors2007In: BMC Genomics, ISSN 1471-2164, E-ISSN 1471-2164, Vol. 8, p. 304-Article in journal (Refereed)
    Abstract [en]

    Background

    With the advent of microarray technology, it has become feasible to identify virtually all genes in an organism that are induced by developmental or environmental changes. However, relying solely on gene expression data may be of limited value if the aim is to infer the underlying genetic networks. Development of computational methods to combine microarray data with other information sources is therefore necessary. Here we describe one such method.

    Results

    By means of our method, previously published Arabidopsis microarray data from cold acclimated plants at six different time points, promoter motif sequence data extracted from ~24,000 Arabidopsis promoters and known transcription factor binding sites were combined to construct a putative genetic regulatory interaction network. The inferred network includes both previously characterised and hitherto un-described regulatory interactions between transcription factor (TF) genes and genes that encode other TFs or other proteins. Part of the obtained transcription factor regulatory network is presented here. More detailed information is available in the additional files.

    Conclusion

    The rule-based method described here can be used to infer genetic networks by combining data from microarrays, promoter sequences and known promoter binding sites. This method should in principle be applicable to any biological system. We tested the method on the cold acclimation process in Arabidopsis and could identify a more complex putative genetic regulatory network than previously described. However, it should be noted that information on specific binding sites for individual TFs were in most cases not available. Thus, gene targets for the entire TF gene families were predicted. In addition, the networks were built solely by a bioinformatics approach and experimental verifications will be necessary for their final validation. On the other hand, since our method highlights putative novel interactions, more directed experiments could now be performed.

  • 7.
    Curtsdotter, Alva
    et al.
    University of Skövde, School of Bioscience. Department of Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden / Department of Environmental Sciences, Emory University, Atlanta, GA, Georgia, United States.
    Banks, H. Thomas
    Center for Research in Scientific Computation, North Carolina State University, Raleigh, NC, United States.
    Banks, John E.
    Undergraduate Research Opportunities Center (UROC), California State University, Monterey Bay, Seaside, CA, United States.
    Jonsson, Mattias
    Department of Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Jonsson, Tomas
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre. Department of Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden .
    Laubmeier, Amanda N.
    Center for Research in Scientific Computation, North Carolina State University, Raleigh, NC, United States.
    Traugott, Michael
    Mountain Agriculture Research Unit, Institute of Ecology, University of Innsbruck, Innsbruck, Austria.
    Bommarco, Riccardo
    Department of Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Ecosystem function in predator-prey food webs: confronting dynamic models with empirical data2019In: Journal of Animal Ecology, ISSN 0021-8790, E-ISSN 1365-2656, Vol. 88, no 2, p. 196-210Article in journal (Refereed)
    Abstract [en]

    Most ecosystem functions and related services involve species interactions across trophic levels, for example, pollination and biological pest control. Despite this, our understanding of ecosystem function in multitrophic communities is poor, and research has been limited to either manipulation in small communities or statistical descriptions in larger ones. Recent advances in food web ecology may allow us to overcome the trade-off between mechanistic insight and ecological realism. Molecular tools now simplify the detection of feeding interactions, and trait-based approaches allow the application of dynamic food web models to real ecosystems. We performed the first test of an allometric food web model's ability to replicate temporally nonaggregated abundance data from the field and to provide mechanistic insight into the function of predation. We aimed to reproduce and explore the drivers of the population dynamics of the aphid herbivore Rhopalosiphum padi observed in ten Swedish barley fields. We used a dynamic food web model, taking observed interactions and abundances of predators and alternative prey as input data, allowing us to examine the role of predation in aphid population control. The inverse problem methods were used for simultaneous model fit optimization and model parameterization. The model captured >70% of the variation in aphid abundance in five of ten fields, supporting the model-embodied hypothesis that body size can be an important determinant of predation in the arthropod community. We further demonstrate how in-depth model analysis can disentangle the likely drivers of function, such as the community's abundance and trait composition. Analysing the variability in model performance revealed knowledge gaps, such as the source of episodic aphid mortality, and general method development needs that, if addressed, would further increase model success and enable stronger inference about ecosystem function. The results demonstrate that confronting dynamic food web models with abundance data from the field is a viable approach to evaluate ecological theory and to aid our understanding of function in real ecosystems. However, to realize the full potential of food web models, in ecosystem function research and beyond, trait-based parameterization must be refined and extended to include more traits than body size. © 2018 The Authors. Journal of Animal Ecology © 2018 British Ecological Society

  • 8.
    Deo, Ameya
    University of Skövde, School of Life Sciences.
    Normalization of microRNA expression levels in Quantitative RT-PCR arrays2010Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Background: Real-time quantitative Reverse Transcriptase Polymerase Chain Reaction (qRT-PCR) is recently used for characterization and expression analysis of miRNAs. The data from such experiments need effective analysis methods to produce reliable and high-quality data. For the miRNA prostate cancer qRT-PCR data used in this study, standard housekeeping normalization method fails due to non-stability of endogenous controls used. Therefore, identifying appropriate normalization method(s) for data analysis based on other data driven principles is an important aspect of this study.

    Results: In this study, different normalization methods were tested, which are available in the R packages Affy and qpcrNorm for normalization of the raw data. These methods reduce the technical variation and represent robust alternatives to the standard housekeeping normalization method. The performance of different normalization methods was evaluated statistically and compared against each other as well as with the standard housekeeping normalization method. The results suggest that qpcrNorm Quantile normalization method performs best for all methods tested.

    Conclusions: The qpcrNorm Quantile normalization method outperforms the other normalization methods and standard housekeeping normalization method, thus proving the hypothesis of the study. The data driven methods used in this study can be applied as standard procedures in cases where endogenous controls are not stable.

  • 9.
    Fagerlind, Magnus
    et al.
    University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Bioscience.
    Stålhammar, Hans
    VikingGenetics, Skara.
    Olsson, Björn
    University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Bioscience.
    Klinga-Levan, Karin
    University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Bioscience.
    Expression of miRNAs in Bull Spermatozoa Correlates with Fertility Rates2015In: Reproduction in domestic animals, ISSN 0936-6768, E-ISSN 1439-0531, Vol. 50, no 4, p. 587-594Article in journal (Refereed)
  • 10.
    Feldhahn, Magdalena
    et al.
    University of Tübingen, Center for Bioinformatics, Applied Bioinformatics, Sand 14, 72076 Tübingen, Germany.
    Dönnes, Pierre
    University of Skövde, School of Life Sciences. University of Skövde, The Systems Biology Research Centre.
    Schubert, Benjamin
    University of Tübingen, Center for Bioinformatics, Applied Bioinformatics, Sand 14, 72076 Tübingen, Germany.
    Schilbach, Karin
    University Children's Hospital, Department of, Hematology/Oncology, Hoppe-Seyler Str. 1, 72076, Tübingen, Germany.
    Rammensee, Hans-Georg
    University of Tübingen, Department of Immunology, Auf der Morgenstelle 15, 72076 Tuebingen, Germany.
    Kohlbacher, Oliver
    University of Tübingen, Center for Bioinformatics, Applied Bioinformatics, Sand 14, 72076 Tübingen, Germany / University of Tübingen, Quantitative Biology Center, Tübingen, Germany.
    miHA-Match: Computational detection of tissue-specific minor histocompatibility antigens2012In: JIM - Journal of Immunological Methods, ISSN 0022-1759, E-ISSN 1872-7905, Vol. 386, no 1-2, p. 94-100Article in journal (Refereed)
    Abstract [en]

    Allogenic stem cell transplantation has shown considerable success in a number of hematological malignancies, in particular in leukemia. The beneficial effect is mediated by donor T cells recognizing patient-specific HLA-binding peptides. These peptides are called minor histocompatibility antigens (miHAs) and are typically caused by single nucleotide polymorphisms. Tissue-specific miHAs have successfully been used in anti-tumor therapy without causing unspecific graft-versus-host reactions. However, only a small number of miHAs have been identified to date, limiting the clinical use.

    Here we present an immunoinformatics pipeline for the identification of miHAs. The pipeline can be applied to large-scale miHA screening, for example, in the development of diagnostic tests. Another interesting application is the design of personalized miHA-based cancer therapies based on patient-donor pair-specific miHAs detected by this pipeline. The suggested method covers various aspects of genetic variant detection, effects of alternative transcripts, and HLA-peptide binding. A comparison of our computational pipeline and experimentally derived datasets shows excellent agreement and coverage of the computationally predicted miHAs.

  • 11.
    Gamalielsson, Jonas
    et al.
    University of Skövde, School of Humanities and Informatics.
    Olsson, Björn
    University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Life Sciences.
    Gene Ontology-based Semantic Alignment of Biological Pathways by Evolutionary Search2008In: Journal of Bioinformatics and Computational Biology, ISSN 0219-7200, E-ISSN 1757-6334, Vol. 6, no 4, p. 825-842Article in journal (Refereed)
    Abstract [en]

    A large number of biological pathways have been elucidated recently, and there is a need for methods to analyze these pathways. One class of methods compares pathways semantically in order to discover parts that are evolutionarily conserved between species or to discover intraspecies similarities. Such methods usually require that the topologies of the pathways being compared are known, i.e. that a query pathway is being aligned to a model pathway. However, sometimes the query only consists of an unordered set of gene products. Previous methods for mapping sets of gene products onto known pathways have not been based on semantic comparison of gene products using ontologies or other abstraction hierarchies. Therefore, we here propose an approach that uses a similarity function defined in Gene Ontology (GO) terms to find semantic alignments when comparing paths in biological pathways where the nodes are gene products. A known pathway graph is used as a model, and an evolutionary algorithm (EA) is used to evolve putative paths from a set of experimentally determined gene products. The method uses a measure of GO term similarity to calculate a match score between gene products, and the fitness value of each candidate path alignment is derived from these match scores. A statistical test is used to assess the significance of evolved alignments. The performance of the method has been tested using regulatory pathways for S. cerevisiae and M. musculus.

  • 12.
    Gamalielsson, Jonas
    et al.
    University of Skövde, School of Humanities and Informatics.
    Olsson, Björn
    University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Humanities and Informatics.
    On the (lack of) robustness of gene expression data clustering2004In: WSEAS Transactions on Biology and Biomedicine, ISSN 1109-9518, E-ISSN 2224-2902, Vol. 1, no 2, p. 198-204Article in journal (Refereed)
    Abstract [en]

    We assess the robustness of partitional clustering algorithms applied to gene expression data. A number of clusterings are made with identical parameter settings and input data using SOM and  k-means algorithms, which both rely on random initialisation and may produce different clusterings with different seeds. We define a reproducibility index and use it to assess the algorithms. The index is based on the number of pairs of genes consistently clustered together in different clusterings. The effect of noise applied to the original data is also studied. Our results show a lack of robustness for both classes of algorithms, with slightly higher reproducibility for SOM than for k-means.

  • 13.
    Geirardsdottir, Kristin
    University of Skövde, School of Humanities and Informatics.
    Identifying and analysing alternative splice variants by aligning ESTs and mRNAs to the genomic sequence2005Independent thesis Advanced level (degree of Master (One Year))Student thesis
    Abstract [en]

    Questions have been raised about the genomic complexity of the human genome, since it was reported that it only consisted of 32,000 genes. Alternative splicing is considered the explanation of the enormous difference between the number of genes and the number of proteins. Aligning expressed sequence tags (ESTs) to the genomic sequence has become a popular approach for gene prediction, revealing alternative splice variants. The aim in this thesis is to identify and analyse splice variants of the adhesion family of G protein-coupled receptors using EST data. 75% of the genes in the data set of 33 sequences were found to have a total of 51 splice variants. About half of the variants were considered functional.

  • 14.
    Gusenleitner, Daniel
    University of Skövde, School of Life Sciences.
    In silico modeling for uncertain biochemical data2009Independent thesis Advanced level (degree of Master (One Year)), 15 credits / 22,5 HE creditsStudent thesis
    Abstract [en]

    Analyzing and modeling data is a well established research area and a vast variety of different methods have been developed over the last decades. Most of these methods assume fixed positions of data points; only recently uncertainty in data has caught attention as potentially useful source of information. In order to provide a deeper insight into this subject, this thesis concerns itself with the following essential question: Can information on uncertainty of feature values be exploited to improve in silico modeling? For this reason a state-of-art random forest algorithm is developed using Matlab R. In addition, three techniques of handling uncertain numeric features are presented and incorporated in different modified versions of random forests. To test the hypothesis six realworld data sets were provided by AstraZeneca. The data describe biochemical features of chemical compounds, including the results of an Ames test; a widely used technique to determine the mutagenicity of chemical substances. Each of the datasets contains a single uncertain numeric feature, represented as an expected value and an error estimate. Themodified algorithms are then applied on the six data sets in order to obtain classifiers, able to predict the outcome of an Ames test. The hypothesis is tested using a paired t-test and the results reveal that information on uncertainty can indeed improve the performance of in silico models.

  • 15.
    Helgadóttir, Hanna Sigrún
    University of Skövde, School of Humanities and Informatics.
    Using semantic similarity measures across Gene Ontology to predict protein-protein interactions2005Independent thesis Basic level (degree of Bachelor)Student thesis
    Abstract [en]

    Living cells are controlled by proteins and genes that interact through complex molecular pathways to achieve a specific function. Therefore, determination of protein-protein interaction is fundamental for the understanding of the cell’s lifecycle and functions. The function of a protein is also largely determined by its interactions with other proteins. The amount of protein-protein interaction data available has multiplied by the emergence of large-scale technologies for detecting them, but the drawback of such measures is the relatively high amount of noise present in the data. It is time consuming to experimentally determine protein-protein interactions and therefore the aim of this project is to create a computational method that predicts interactions with high sensitivity and specificity. Semantic similarity measures were applied across the Gene Ontology terms assigned to proteins in S. cerevisiae to predict protein-protein interactions. Three semantic similarity measures were tested to see which one performs best in predicting such interactions. Based on the results, a method that predicts function of proteins in connection with connectivity was devised. The results show that semantic similarity is a useful measure for predicting protein-protein interactions.

  • 16.
    Hellner, Qarin
    University of Skövde, School of Life Sciences.
    Simultaneous MSY management of a predator and prey species, the Cod (Gadus morhua) and Herring (Clupea harengus) in the Baltic Sea2012Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The European Commission manages fish stocks by applying a fishing mortality based on the maximum sustainable yield concept. So far most Baltic Sea fishing maximum sustainable yieldmodels have focused on one species at a time. The few existing multi-species models have assumed that a species’ maturity and growth is dependent on the availability of food. Our two-species models make it possible to investigate if there is a conflict between fishing maximum sustainable yield for cod and herring in the Baltic Sea. This two-species model of cod, as a predator and herring as prey, takes into account environmental drivers on cod and herring recruitment. Reproductive volume together with year-growth, (a year specific effect on growth of external variables like food availability) and predation by grey seals was included in the cod model. The herring model was dependent on cod spawning stock biomass and year-growth. The result shows that the reproductive volume is the main factor that affects the maximum sustainable yield for cod. The spawning stock biomass at maximum sustainable yield is more sensitive to reproductive volume than year-growth. When predation from seals is added in mortality and high environmental factors occurs the spawning stock biomass would be 50% compared to the spawning stock biomass at high environmental effects without seal predation. Four simulations of high cod spawning stock biomass were devastating for the herring population that was eradicated with high predation pressure. The herring maximum sustainable yield depends on the amount of cod spawning stack biomass i.e. the effect of high or low reproductive volume. Two analyses were made on a current environmental state for both species. The first analysis had a natural mortality of 0.2 for cod, which gave an fishing mortality of 0.20 and maximum sustainable yield of 410 000 tons. The herring had a fishing mortality of 0.03 and maximum sustainable yield of 11 000 tons. The second simulation included seal predation in cod mortality which decreased the cod maximum sustainable yield by 98% at a fishing mortality of 0.02, which gave a fishing mortality of 0.19 and maximum sustainable yield of 275 000 tons for herring. This gives a 25 times increase of herring maximum sustainable yield compared to the result without predation on cod. The cod population dynamics is vulnerable to environmental changes and to secure a healthy and productive cod population the target fishing mortality should be kept in phase with current reproductive volume. 

  • 17.
    Holmgren, Gustav
    Sahlgrenska Academy at University of Gothenburg.
    In vitro toxicity testing using human pluripotent stem cell derivatives2016Doctoral thesis, comprehensive summary (Other academic)
  • 18.
    Jadhav, Trishul
    University of Skövde, School of Life Sciences.
    Knowledge Based Gene Set analysis (KB-GSA): A novel method for gene expression analysis2010Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Microarray technology allows measurement of the expression levels of thousand of genes simultaneously. Several gene set analysis (GSA) methods are widely used for extracting useful information from microarrays, for example identifying differentially expressed pathways associated with a particular biological process or disease phenotype. Though GSA methods like Gene Set Enrichment Analysis (GSEA) are widely used for pathway analysis, these methods are solely based on statistics. Such methods can be awkward to use if knowledge of specific pathways involved in particular biological processes are the aim of the study. Here we present a novel method (Knowledge Based Gene Set Analysis: KB-GSA) which integrates knowledge about user-selected pathways that are known to be involved in specific biological processes. The method generates an easy to understand graphical visualization of the changes in expression of the genes, complemented with some common statistics about the pathway of particular interest.

  • 19.
    Jansson, Andreas
    University of Skövde, School of Life Sciences.
    Modelling T helper cell activation and development2006Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    T helper (Th) cell activation and development is one of the most critical events in regulating the adaptive immune response. Understanding its regulation could be of great therapeutical value as many severe diseases are associated with failure in controlling T cell activation and development. However, the regulation of T cell activation appears to be one of the most complex set of cellular and molecular interactions known in the immune system. There is therefore an urgent need for tools to unravel this complexity, and to make use of the quantitative experimental data. To address this issue, mathematical and computational models, based on rigorous biophysical and kinetic data, were developed to study the specific role of some of the major costimulatory molecules involved in Th cell activation, and others developed to investigate proposed theories about mechanisms involved in Th cell differentiation. The simulations of costimulation reveal new implications for the function of the costimulatory molecules CD28 and CTLA-4, and their ligands B7-1 and B7-2, and show how binding affinity, stoichiometric properties, expression levels, and, in particular, competition effects, all profoundly influence complex formation at the immunological synapse. The results support the concept that B7-2 and B7-1 are the dominant ligands of CD28 and CTLA-4, respectively, and indicate that the inability of B7-2 to recruit CTLA-4 to the synapse cannot be, as has been previously proposed, due to the different binding properties of B7-1 and B7-2. Simulations of Th cell development reveal that both instructive and selective processes are likely to be involved in Th cell differentiation. In addition, further simulations indicate that Th2 cells are more likely to become dominant by inhibiting Th1 cells (negative selection), rather than selecting their own growth (positive selection). This thesis also includes an experimental work in which the immunomodulatory role of the bacterial signalling molecule N-3-(oxododecanoyl)-L-homoserine lactone (OdDHL) was analysed. This study strongly suggests that OdDHL suppresses Th cell activation and development, and that it is likely targeting the intracellular signalling events involved in the early stages of Th cell activation.

  • 20.
    Jantscher, Yvonne
    University of Skövde, School of Life Sciences. University of Skövde.
    Identification of miRNAs and their target genes in stem cell derived cardiomyocytes2011Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Stem cell research, especially the one dealing with human embryonic stem cells, is a major topic nowadays. In the last few years studies about human embryonic stem cell derived cardiomyocytes highlighted the importance of those, as their characteristics are almost identical as of the cardiomyocytes in the heart (i.e. the contraction of those cells). The studies concentrate on the ability of using cardiomyocytes in the drug development for cardiac diseases or in regenerative medicine and cell replacement therapies. In contrast some researchers concentrate on microRNAs (miRNAs) as regulators in the development of cardiomyocytes. This study combines both research topics as it deals with stem cells and miRNAs (as well as their target mRNAs). A main objective is to find differentially expressed genes by using Significance Analysis of Microarrays (SAM) as method. Furthermore miRNA target prediction is applied and the identified targets are compared with the ones found by SAM. With an intersection approach we derived 41 targets of up-regulated miRNAs and 25 targets of down-regulated miRNAs, which can be the basis for further studies (i.e. knock-out experiments).

  • 21.
    Johansson, Lennart F.
    et al.
    University Medical Center Groningen, The Netherlands.
    de Weerd, Hendrik A.
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre. University Medical Center Groningen, The Netherlands.
    de Boer, Eddy N.
    University Medical Center Groningen, The Netherlands.
    van Dijk, Freerk
    University Medical Center Groningen, The Netherlands.
    Te Meerman, Gerard J.
    University Medical Center Groningen, The Netherlands.
    Sijmons, Rolf H.
    University Medical Center Groningen, The Netherlands.
    Sikkema-Raddatz, Birgit
    University Medical Center Groningen, The Netherlands.
    Swertz, Morris A.
    University Medical Center Groningen, The Netherlands.
    NIPTeR: an R package for fast and accurate trisomy prediction in non-invasive prenatal testing2018In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 19, no 1, article id 531Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Various algorithms have been developed to predict fetal trisomies using cell-free DNA in non-invasive prenatal testing (NIPT). As basis for prediction, a control group of non-trisomy samples is needed. Prediction accuracy is dependent on the characteristics of this group and can be improved by reducing variability between samples and by ensuring the control group is representative for the sample analyzed.

    RESULTS: NIPTeR is an open-source R Package that enables fast NIPT analysis and simple but flexible workflow creation, including variation reduction, trisomy prediction algorithms and quality control. This broad range of functions allows users to account for variability in NIPT data, calculate control group statistics and predict the presence of trisomies.

    CONCLUSION: NIPTeR supports laboratories processing next-generation sequencing data for NIPT in assessing data quality and determining whether a fetal trisomy is present. NIPTeR is available under the GNU LGPL v3 license and can be freely downloaded from https://github.com/molgenis/NIPTeR or CRAN.

  • 22.
    Krus Hansson, Eric
    University of Skövde, School of Bioscience.
    Default Mode Network and Its Role in Major Depressive Disorder2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This essay investigates the relationship between a malfunctioning Default Mode Network (DMN) and the diagnosis of Major Depressive Disorder (MDD). A deeper understanding of how the DMN affects those brain processes which are implicated in MDD may offer new approaches to reduce the suffering of the very large number of MDD-afflicted patients. The MDD-DMN relationship has been investigated by studying scientific articles within the field of cognitive neuroscience and searching the articles for clues on how a malfunctioning DMN might correlate with the diagnosis of MDD. The essay concludes that there is much experimental evidence in support of there being a strong coupling between a malfunctioning DMN and the diagnosis of MDD.

  • 23.
    Lagervik Öster, Alice
    University of Skövde, School of Humanities and Informatics.
    Probability calculations of orthologous genes2005Independent thesis Basic level (degree of Bachelor)Student thesis
    Abstract [en]

    The aim of this thesis is to formulate and implement an algorithm that calculates the probability for two genes being orthologs, given a gene tree and a species tree. To do this, reconciliations between the gene tree and the species trees are used. A birth and death process is used to model the evolution, and used to calculate the orthology probability. The birth and death parameters are approximated with a Markov Chain Monte Carlo (MCMC). A MCMC framework for probability calculations of reconciliations written by Arvestad et al. (2003) is used. Rules for orthologous reconciliations are developed and implemented to calculate the probability for the reconciliations that have two genes as orthologs. The rules where integrated with the Arvestad et al. (2003) framework, and the algorithm was then validated and tested.

  • 24.
    Lantz, Mikael
    University of Skövde, School of Humanities and Informatics.
    A targeted evaluation of OpenEye’s methods for virtual ligand screens and docking2005Independent thesis Advanced level (degree of Master (One Year))Student thesis
    Abstract [en]

    The process of drug discovery is very slow and expensive. There is a need for reliable in silico methods; however the performance of these methods differs.

    This work presents a targeted study on how the drug discovery methods used in OpenEye’s tools ROCS, EON and FRED perform on targets with small ligands. It was examined if 12 compounds (markers) somewhat similar to AMP could be detected by ROCS in a random data set comprised of 1000 compounds. It was also examined if EON could find any electrostatic similarities between the queries and the markers. The performance of FRED with respect to re-generation of bound ligand modes was examined on ten different protein/ligand complexes from the Brookhaven Protein Data Bank. It was also examined if FRED is suitable as a screening tool since several other docking methods are used in such a way. Finally it was also examined if it was possible to reduce the time requirements of ROCS when running multiconformer queries by using a combination of single conformer queries coupled with multiconformer queries.

    The conclusions that could be drawn from this project were that FRED is not a good screening tool, but ROCS performs well as such. It was also found that the scoring functions are the weak spots of FRED. EON is probably very sensitive to the conformers used but can in some cases strengthen the results from ROCS. A novel and simple way to reduce the time complexity with multiconformer queries to ROCS was discovered and was shown to work well.

  • 25.
    Levefelt, Christer
    et al.
    University of Skövde, School of Humanities and Informatics.
    Lundh, Dan
    University of Skövde, School of Humanities and Informatics.
    A fold-recognition approach to loop modeling2006In: Journal of Molecular Modeling, ISSN 1610-2940, E-ISSN 0948-5023, Vol. 12, no 2, p. 125-139Article in journal (Refereed)
    Abstract [en]

    A novel approach is proposed for modeling loop regions in proteins. In this approach, a prerequisite sequence-structure alignment is examined for regions where the target sequence is not covered by the structural template. These regions, extended with a number of residues from adjacent stem regions, are submitted to fold recognition. The alignments produced by fold recognition are integrated into the initial alignment to create an alignment between the target sequence and several structures, where gaps in the main structural template are covered by local structural templates. This one-to-many (1:N) alignment is used to create a protein model by existing protein-modeling techniques. Several alternative approaches were evaluated using a set of ten proteins. One approach was selected and evaluated using another set of 31 proteins. The most promising result was for gap regions not located at the C-terminus or N-terminus of a protein, where the method produced an average RMSD 12% lower than the loop modeling provided with the program MODELLER. This improvement is shown to be statistically significant.

  • 26.
    Lindlöf, Angelica
    University of Skövde, Department of Computer Science.
    Deriving Genetic Networks from Gene Expression Data and Prior Knowledge2001Independent thesis Advanced level (degree of Master (One Year))Student thesis
    Abstract [en]

    In this work three different approaches for deriving genetic association networks were tested. The three approaches were Pearson correlation, an algorithm based on the Boolean network approach and prior knowledge. Pearson correlation and the algorithm based on the Boolean network approach derived associations from gene expression data. In the third approach, prior knowledge from a known genetic network of a related organism was used to derive associations for the target organism, by using homolog matching and mapping the known genetic network to the related organism. The results indicate that the Pearson correlation approach gave the best results, but the prior knowledge approach seems to be the one most worth pursuing

  • 27.
    Lindlöf, Angelica
    University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Life Sciences.
    In the quest for a cold tolerant variety: gene expression profile analysis of cold stressed oat and rice2008Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Cold acclimation is a process which increases the freezing tolerance of an organism, after exposure to low, non-freezing temperatures. The acclimation ensures that cold tolerant species can endure harsh winter conditions, by preparing them to sub-zero temperatures. Cold-sensitive plants such as oat and rice have limited abilities to cold acclimate and are therefore easily damaged during winter time.

     

    The development of more tolerant varieties by using biotechnological methods is desirable, since the yields are expected to improve due to a prolonged vegetation period. However, in order to apply such methods, more knowledge about the underlying mechanisms regulating the cold tolerance and acclimation is required. One step in this direction is to analyze gene expression data generated from cold stressed oat (Part I) and rice plants (Part II).

     

    The focus of this thesis is, consequently, analysis of expression profiling data, which was generated using the EST sequencing and cDNA microarray technologies. The results show that both oat and rice are cold responsive,with many of the previously identified cold regulated genes having a counterpart in these species. In rice, however, the response is less dynamic than in the model organism Arabidopsis thaliana and this may explain its inability to fully cold acclimate.

     

     

     

    Additionally, the work in this thesis focuses on evaluating if small-scale EST sets can be used for ‘digital-Northern’, in order to identify genes that are involved in the regulation of the cold stress response. The results show that small-scaled EST sets are not optimal for such an analysis, since the method detected only a portion of cold responsive genes represented in the sets. This has to due with the inherent properties of EST data and limitations in the analysis steps of the sequences.

     

    The work also concerns the identification of cis-elements coupled to transcription factors prominent in the regulation of the response. Since cold acclimation is a quantitative trait the response and regulation of cold stress is under combinatorial control of several transcription factors and the results show that this should be taken into account when identifying binding sites.

  • 28.
    Lindlöf, Angelica
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Systems Biology Research Centre.
    Bräutigam, Marcus
    Göteborg University.
    Chawade, Aakash
    Göteborg University.
    Olsson, Olof
    Göteborg University.
    Olsson, Björn
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Systems Biology Research Centre. Bioinformatik, Bioinformatics.
    Evaluation of combining several statistical methods with a flexible cutoff for identifying differentially expressed genes in pairwise comparison of EST sets2008In: Bioinformatics and Biology Insights, ISSN 1177-9322, E-ISSN 1177-9322, Vol. 2, p. 215-237Article in journal (Refereed)
    Abstract [en]

    The detection of differentially expressed genes from EST data is of importance for the discovery of potential biological or pharmaceutical targets, especially when studying biological processes in less characterized organisms and where large-scale microarrays are not an option. We present a comparison of five different statistical methods for identifying up-regulated genes through pairwise comparison of EST sets, where one of the sets is generated from a treatment and the other one serves as a control. In addition, we specifically address situations where the sets are relatively small (~2,000– 10,000 ESTs) and may differ in size. The methods were tested on both simulated and experimentally derived data, and compared to a collection of cold stress induced genes identified by microarrays. We found that combining the method pro- posed by Audic and Claverie with Fisher’s exact test and a method based on calculating the difference in relative frequency was the best combination for maximizing the detection of up-regulated genes. We also introduced the use of a flexible cutoff, which takes the size of the EST sets into consideration. This could be considered as an alternative to a static cutoff. Finally, the detected genes showed a low overlap with those identified by microarrays, which indicates, as in previous studies, low overall concordance between the two platforms.

  • 29.
    Lindlöf, Angelica
    et al.
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Chawade, Aakash
    CropTailor AB, Department of Pure and Applied Biochemistry, Lund University, Lund, Sweden / Department of Immunotechnology, Lund University, Lund, Sweden.
    Sikora, Per
    Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden.
    Olsson, Olof
    CropTailor AB, Department of Pure and Applied Biochemistry, Lund University, Lund, Sweden / Department of Pure and Applied Biochemistry, Lund University, Lund, Sweden.
    Comparative Transcriptomics of Sijung and Jumli Marshi Rice during Early Chilling Stress Imply Multiple Protective Mechanisms2015In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 10, no 5, article id e0125385Article in journal (Refereed)
    Abstract [en]

    Introduction

    Low temperature is one of the major environmental factors that adversely affect plant growth and yield. Many cereal crops from tropical regions, such as rice, are chilling sensitive and, therefore, are affected already at <10°C. Interestingly, it has been demonstrated that chilling susceptibility varies greatly among rice varieties, which indicates differences in the underlying molecular responses. Understanding these differences is vital for continued development of rational breeding and transgenic strategies for more tolerant varieties. Thus, in this study, we conducted a comparative global gene expression profiling analysis of the chilling tolerant varieties Sijung and Jumli Marshi (spp. Japonica) during early chilling stress (<24 h, 10°C).

    Methods and Results

    Global gene expression experiments were conducted with Agilent Rice Gene Expression Microarray 4x44K. The analysed results showed that there was a relatively low (percentage or number) overlap in differentially expressed genes in the two varieties and that substantially more genes were up-regulated in Jumli Marshi than in Sijung but the number of down-regulated genes were higher in Sijung. In broad GO annotation terms, the activated response pathways in Sijung and Jumli Marshi were coherent, as a majority of the genes belonged to the catalytic, transcription regulator or transporter activity categories. However, a more detailed analysis revealed essential differences. For example, in Sijung, activation of calcium and phosphorylation signaling pathways, as well as of lipid transporters and exocytosis-related proteins take place very early in the stress response. Such responses can be coupled to processes aimed at strengthening the cell wall and plasma membrane against disruption. On the contrary, in Jumli Marshi, sugar production, detoxification, ROS scavenging, protection of chloroplast translation, and plausibly the activation of the jasmonic acid pathway were the very first response activities. These can instead be coupled to detoxification processes.

    Conclusions

    Based on the results inferred from this study, we conclude that different, but overlapping, strategies are undertaken by the two varieties to cope with the chilling stress; in Sijung the initial molecular responses seem to be mainly targeted at strengthening the cell wall and plasma membrane, whereas in Jumli Marshi the protection of chloroplast translation and detoxification is prioritized.

  • 30.
    Liu, Oscar H.
    University of Skövde, School of Bioscience.
    RNAseq Analysis of Gastric Bacteria in Helicobacter pylori-Associated Carcinogenesis2014Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Helicobacter pylori infects more than half of the world's population, and is known to be involved in several diseases including gastric cancer. Its close interactions with the stomach and host immune system serves as a good model to study the co-adaptation and co-evolution of the organisms in the stomach micro-environment. In this project, we utilized RNA-seq and data analysis tools to investigate differentially expressed genes by H. pylori in patients at different stages of early gastric cancer development. We also investigated the abundance and diversity of bacterial genera other than H. pylori, and looked for correlations with H. pylori presence and number. For differential gene expression of H. pylori, one gene was differentially expressed between samples of corpus atrophy without metaplasia vs. samples of antrum gastritis, and eight genes were found to be differentially expressed between samples of corpus atrophy with metaplasia vs. samples with pan-gastritis. When samples were clustered into different groups based on the expression data, 52 genes (shared or unique to the specific comparison groups) were found to be differentially expressed, but no apparent patterns were observed that could be explained by medical or sample collection data. For bacterial diversity and abundances, we found several genera colonizing the stomach, of which some have been previously identified. While most of these bacteria colonize regardless of the presence of H. pylori, the abundance of three genera, Wolinella, Campylobacter, and Veillonella, seem to be correlated with the presence of H. pylori.

  • 31.
    Liu, Oscar H.
    University of Skövde, School of Bioscience.
    RNAseq Analysis of Gastric Bacteria in Helicobacter pylori-Associated Carcinogenesis2014Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Helicobacter pylori infects more than half of the world's population, and is known to be involved in several diseases including gastric cancer. Its close interactions with the stomach and host immune system serves as a good model to study the co-adaptation and co-evolution of the organisms in the stomach micro-environment. In this project, we utilized RNA-seq and data analysis tools to investigate differentially expressed genes by H. pylori in patients at different stages of early gastric cancer development. We also investigated the abundance and diversity of bacterial genera other than H. pylori, and looked for correlations with H. pylori presence and number. For differential gene expression of H. pylori, one gene was differentially expressed between samples of corpus atrophy without metaplasia vs. samples of antrum gastritis, and eight genes were found to be differentially expressed between samples of corpus atrophy with metaplasia vs. samples with pan-gastritis. When samples were clustered into different groups based on the expression data, 52 genes (shared or unique to the specific comparison groups) were found to be differentially expressed, but no apparent patterns were observed that could be explained by medical or sample collection data. For bacterial diversity and abundances, we found several genera colonizing the stomach, of which some have been previously identified. While most of these bacteria colonize regardless of the presence of H. pylori, the abundance of three genera, Wolinella, Campylobacter, and Veillonella, seem to be correlated with the presence of H. pylori.

  • 32.
    Lubovac, Zelmina
    et al.
    University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Life Sciences.
    Gamalielsson, Jonas
    University of Skövde, School of Humanities and Informatics.
    Olsson, Björn
    University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Life Sciences.
    Combining functional and topological properties to identify core modules in protein interaction networks2006In: Proteins: Structure, Function, and Bioinformatics, ISSN 0887-3585, E-ISSN 1097-0134, Vol. 64, no 4, p. 948-959Article in journal (Refereed)
    Abstract [en]

    Advances in large-scale technologies in proteomics, such as yeast two-hybrid screening and mass spectrometry, have made it possible to generate large Protein Interaction Networks (PINs). Recent methods for identifying dense sub-graphs in such networks have been based solely on graph theoretic properties. Therefore, there is a need for an approach that will allow us to combine domain-specific knowledge with topological properties to generate functionally relevant sub-graphs from large networks. This article describes two alternative network measures for analysis of PINs, which combine functional information with topological properties of the networks. These measures, called weighted clustering coefficient and weighted average nearest-neighbors degree, use weights representing the strengths of interactions between the proteins, calculated according to their semantic similarity, which is based on the Gene Ontology terms of the proteins. We perform a global analysis of the yeast PIN by systematically comparing the weighted measures with their topological counterparts. To show the usefulness of the weighted measures, we develop an algorithm for identification of functional modules, called SWEMODE (Semantic WEights for MODule Elucidation), that identifies dense sub-graphs containing functionally similar proteins. The proposed method is based on the ranking of nodes, i.e., proteins, according to their weighted neighborhood cohesiveness. The highest ranked nodes are considered as seeds for candidate modules. The algorithm then iterates through the neighborhood of each seed protein, to identify densely connected proteins with high functional similarity, according to the chosen parameters. Using a yeast two-hybrid data set of experimentally determined protein-protein interactions, we demonstrate that SWEMODE is able to identify dense clusters containing proteins that are functionally similar. Many of the identified modules correspond to known complexes or subunits of these complexes.

  • 33.
    Lundell, Simon
    University of Skövde, Department of Computer Science.
    Modelling Gene Expression during Ontogenetic Differentiation2001Independent thesis Advanced level (degree of Master (One Year))Student thesis
    Abstract [en]

    Various types of recurrent neural networks have been used as models for the regulatory relationships between genes. The neural network is trained on the data from micro-array techniques, each gene corresponds to a neuron in the network. The data from the micro-array technologies has numerous genes, but usually involves few samples, this makes the network heavily under-determined. In this work we will propose a method that can cope with the poorness of the data. We will use a Hopfield-type neural network to model the ontogenetic differentiation of female honeybees. A method that identifies the genes that determine the castes is proposed.

  • 34.
    Lutimba, Stuart
    University of Skövde, School of Bioscience. Science for Life Laboratory.
    Determination of specificity and affinity of the Lactose permease (LacY) protein of Escherichia coli through application of molecular dynamics simulation2018Independent thesis Advanced level (degree of Master (Two Years)), 40 credits / 60 HE creditsStudent thesis
    Abstract [en]

    Proteins are essential in all living organisms. They are involved in various critical activities and are also structural components of cells and tissues. Lactose permease a membrane protein has become a prototype for the major facilitator super family and utilises an existing electrochemical proton gradient to shuttle galactoside sugars to the cell. Therefore it exists in two principle states exposing the internal binding site to either side of the membrane. From previous studies it has been suggested that protonation precedes substrate binding but it is still unclear why this has to occur in the event of substrate binding. Therefore this study aimed to bridge this gap and to determine the chemical characteristics of the transport pathway. Molecular dynamics simulation methods and specialised simulation hardware were employed to elucidate the dependency of substrate binding on the protonation nature of Lactose permease. Protein models that differed in their conformation as well as their protonation states were defined from their respective X-ray structures. Targeted molecular dynamics was implemented to drive the substrate to the binding site and umbrella sampling was used to define the free energy of the transport pathway. It was therefore suggested that protonation for sugar binding is due to the switch-like mechanism of Glu325 in the residue-residue interaction (His322 and Glu269) that leads to sugar binding only in the protonated state of LacY. Furthermore, the free energy profile of sugar transport path way was lower only in the protonated state which indicates stability of sugar binding in the protonated state.

  • 35.
    Martinez Maestre, Andreu
    University of Skövde, School of Bioscience.
    PVC: Proximity Value Clustering: A new clustering method without human interaction2018Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
  • 36.
    Martínez Enguita, David
    University of Skövde, School of Bioscience.
    Identification of personalized multi-omic disease modules in asthma2018Independent thesis Advanced level (degree of Master (Two Years)), 40 credits / 60 HE creditsStudent thesis
    Abstract [en]

    Asthma is a respiratory syndrome associated with airflow limitation, bronchial hyperresponsiveness and inflammation of the airways in the lungs. Despite the ongoing research efforts, the outstanding heterogeneity displayed by the multiple forms in which this condition presents often hampers the attempts to determine and classify the phenotypic and endotypic biological structures at play, even when considering a limited assembly of asthmatic subjects. To increase our understanding of the molecular mechanisms and functional pathways that govern asthma from a systems medicine perspective, a computational workflow focused on the identification of personalized transcriptomic modules from the U-BIOPRED study cohorts, by the use of the novel MODifieR integrated R package, was designed and applied. A feature selection of candidate asthma biomarkers was implemented, accompanied by the detection of differentially expressed genes across sample categories, the production of patient-specific gene modules and the subsequent construction of a set of core disease modules of asthma, which were validated with genomic data and analyzed for pathway and disease enrichment. The results indicate that the approach utilized is able to reveal the presence of components and signaling routes known to be crucially involved in asthma pathogenesis, while simultaneously uncovering candidate genes closely linked to the latter. The present project establishes a valuable pipeline for the module-driven study of asthma and other related conditions, which can provide new potential targets for therapeutic intervention and contribute to the development of individualized treatment strategies.

  • 37.
    Moberg, Erik
    University of Skövde, School of Humanities and Informatics.
    Prototyp som stöd åt implementeringen2005Independent thesis Basic level (degree of Bachelor)Student thesis
    Abstract [sv]

    Programvaruutveckling lider idag av stora problem och många av problemen är kopplade till hur krav samlas in och hanteras. Ett sätt att underlätta kravinsamlingen och att öka kommunikation med kund är att ta fram en prototyp, vilket är en konkret representation av programvaran som ska tas fram. När kravutvinningen har kommit tillräckligt långt kan denna prototyp användas som en del av en kravspecifikation. En vanlig form av kravspecifikation är ett dokument, men även en (exekverbar) prototyp kan vara en effektiv representation av programvaran som ska tas fram.

    I detta arbete undersöks det vilka problem som kan uppstå då en prototyp används som en del av en kravspecifikation. Problem identifieras i litteraturen och intervjuer utförs för att undersöka vilka problem som finns i praktiken. Det visar sig att flera av de problem som litteraturen tar upp inte ses som reella av de respondenter som tillfrågas. Vidare visar det sig att många problem som "borde" uppstå inte gör det på grund av att de tillfrågade organisationerna ofta tillämpar ett mer pragmatiskt än formellt arbetssätt.

  • 38.
    Morland, Sara
    University of Skövde, School of Bioscience.
    Exploring qpcr data with weighted gene coexpression network analysis (WGCNA)2015Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Differently expressed genes e.g. in a disease may play a role in the etiology or progression of the disease. The traditional approach of finding differentially expressed genes is to compare the expression levels in the groups, and produce a list of differentially expressed candidate genes. With many pairwise comparisons, the risk of introducing type I and type II errors is high. One solution is to group together genes that are co-expressed into modules. Weighted gene coexpression network analysis (WGCNA) uses a topological overlap module approach and has been proved to find patterns that have been undetected by gene-to-gene comparison methods. qPCR has high sensitivity and specificity, and advances in technology has increased its throughput. The goal of the project was to construct WGCNA modules from qPCR data and evaluate the WGCNA method in five previously published qPCR data sets. There was little overlap between the differentially expressed genes found in the published articles and the candidates found by WGCNA. In three data sets WGCNA failed to produce any significant genes. In one of the data set significant genes were found where the original article failed. In one data set, 19 out of 60 genes that are top-ranked by the original authors were found in significant WGCNA modules. The biggest challenge with this type of comparison is to determine whether results that differ from the published studies are more or less biologically relevant. It is difficult to draw conclusions on whether the method is suitable for use for analysis of qPCR data based on this study.

  • 39.
    Olsson, Björn E.
    et al.
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Korsakova, Ekaterina S.
    Institute of Ecology and Genetics of Microorganisms, Ural Branch of the Russian Academy of Sciences, Perm, Russia.
    Anan'ina, Lyudmila N.
    Institute of Ecology and Genetics of Microorganisms, Ural Branch of the Russian Academy of Sciences, Perm, Russia.
    Pyankova, Anna A.
    Institute of Ecology and Genetics of Microorganisms, Ural Branch of the Russian Academy of Sciences, Perm, Russia.
    Mavrodi, Olga V.
    Department of Biological Sciences, The University of Southern Mississippi, USA.
    Plotnikova, Elena G.
    Institute of Ecology and Genetics of Microorganisms, Ural Branch of the Russian Academy of Sciences, Perm, Russia.
    Mavrodi, Dmitri V.
    Department of Biological Sciences, The University of Southern Mississippi, USA.
    Draft genome sequences of strains Salinicola socius SMB35T, Salinicola sp. MH3R3–1 and Chromohalobacter sp. SMB17 from the Verkhnekamsk potash mining region of Russia2017In: Standards in Genomic Sciences, ISSN 1944-3277, E-ISSN 1944-3277, Vol. 12, no 39, p. 1-13Article in journal (Refereed)
    Abstract [en]

    Halomonads are moderately halophilic bacteria that are studied as models of prokaryotic osmoadaptation and sources of enzymes and chemicals for biotechnological applications. Despite the progress in understanding the diversity of these organisms, our ability to explain ecological, metabolic, and biochemical traits of halomonads at the genomic sequence level remains limited. This study addresses this gap by presenting draft genomes of Salinicola socius SMB35T, Salinicola sp. MH3R3-1 and Chromohalobacter sp. SMB17, which were isolated from potash mine tailings in the Verkhnekamsk salt deposit area of Russia. The analysis of these genomes confirmed the importance of ectoines and quaternary amines to the capacity of halomonads to tolerate osmotic stress and adapt to hypersaline environments. The study also revealed that Chromohalobacter and Salinicola share 75-90% of the predicted proteome, but also harbor a set of genus-specific genes, which in Salinicola amounted to approximately 0.5 Mbp. These genus-specific genome segments may contribute to the phenotypic diversity of the Halomonadaceae and the ability of these organisms to adapt to changing environmental conditions and colonize new ecological niches.

  • 40.
    Padvitski, Tsimafei
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre. CECAD University of Cologne.
    Integrative analysis of age-related changes in the transcriptome of Caenorhabditis elegans2015Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Ageing is difficult to study because of the complexity and multi-factorial nature of traits that result from a combination of environmental, genetic, epigenetic and stochastic factors, each contributing to the overall phenotype. In light of this challenge, transcriptomic studies of aging organisms are of particular interest, since transcription is an intermediate step that links genotype and phenotype.

    In recent years microarrays have been widely used for elucidation of changes that occur with age in the transcriptome in Caenorhabditis elegans. However, different microarray studies of C. elegans report sets of differentially expressed genes of varying consistence, with different functional annotations. Failures to find a consistent set of transcriptomic alterations may reflect the absence of a specific genetic program that would guide age-related changes but may also, to some extent, be a consequence of a small sample sizes and a lack of study power in transcriptomic researches. To tackle this issue we analyzed RNA sequences of samples from a time-series experiment of normal aging of C. elegans, performing the first, to our knowledge, NGS-based study of such kind. As a result, evidences were collected that promote a union of two competing theories: the theory of DNA damage accumulation and the theory of programmed aging.

    Next, we applied two alternative methods, namely the Short Time-series Expression Mining and the Network Smoothing algorithm, in order to obtain and analyze sets of genes that represent distinct modules of age-related changes in the transcriptome. Besides characterization of age-related changes, we were also interested in assessment and validation of the Network Smoothing algorithm. Generally, results of clustering of smoothed scores are consistent with results of short time-series clustering, allowing robust elucidation of functions that are perturbed during aging.

    At the last phase of the project we questioned if observed changes in the transcriptome can be controlled by specific transcription factors. Thus we used Chip-seq data to predict plausible transcription factor regulators of gene sets obtained using time series clustering and Network smoothing. On the one hand, all predicted transcription factors had documented relevance to aging. On the other hand, we did not achieve gene set specific prediction of transcription factors. In fact, genes with the opposite dynamics were predicted to respond to the same transcription factors. 

    To summarize, we characterized in details age-related changes in the transcriptome of C. elegans, validated the performance of the Network Smoothing algorithm and showed that integration of gene expression with Chip-seq data allows to predict transcription factors that are capable to modulate the lifespan of C. elegans.

  • 41.
    Paramonov, Ida
    University of Skövde, School of Humanities and Informatics.
    Deriving a refined set of housekeeping genes in differentiating human embryonic stem cells2008Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In this thesis project housekeeping genes in differentiating human embryonic stem cells were investigated. Housekeeping genes are involved in basic functions in the cells and are assumed to be expressed at relatively constant levels across different cell types and experimental conditions. Based on these features, housekeeping genes are frequently used as controls in calibration of gene expression data. Commonly used housekeeping genes in somatic tissues have shown to vary notably in human embryonic stem cells and are therefore inappropriate as reference genes in this unique cell type. In the present work a novel set of gene expression data obtained by profiling of undifferentiated and early differentiating cardiac cells, was analyzed. Stably expressed genes were identified in this data set and were subsequently intersected with a previously proposed set of 292 stable genes in human embryonic stem cells. A resulting set of 73 genes show stability across all investigated cell lines and experimental conditions. These genes are suggested as a more reliable set of reference genes in differentiating human embryonic stem cells than frequently used housekeeping genes in somatic tissue. In addition, a novel set of 20 genes was identified as very stably expressed during the differentiation towards the cardiac lineage. After further validation of stability with RT-PCR, these genes could be useful as controls in studies of human embryonic stem cells that differentiate towards the cardiac lineage.

  • 42.
    Persson, Emma
    University of Skövde, School of Bioscience.
    Developing a web based tool for identification of disease modules2018Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Complex diseases such as cancer or obesity are thought to be caused by abnormalities in multiple  genes and cannot be derived to one specific location in the genome. It has been shown that  identification of disease associated genes can be made through looking at interaction patterns in a  protein‐protein interaction network, where the disease associated genes are represented in clusters,  or disease modules. There are several algorithms developed to infer these disease modules, but  studies have shown that the reliability of the results increase if multiple algorithms are used and a  consensus module is derived from them. MODifieR is an R package developed to combine the results  of multiple  disease module inferring algorithms and has proven to provide a stable result. To  increase usability of the R package and make it available not only for users with programmatic skills,  MODifieR Web was developed as a web based tool with a graphical user interface. The tool was built  using Angular and .NET core, invoking the MODifieR R package in the backend. The interface requires  input in the form of an expression matrix and a probe map from the user, easily uploadable in a  drag‐and‐drop  interface.  It  gives  the  user  the  possibility  to  analyze  data  using  seven  different  algorithms and provide results as gene lists and visualizes the consensus module in a network image.  MODifieR Web is a first version of an application that is a novel contribution to the existing tools for  identification of disease modules, although in need of further improvements to be able to serve a  greater  pool  of  users  in  a  more  effective  way.  The  tool  is  available  to  try  out  at   http://transbioinfo.liu.se/modifier#/home and the source code is released as an open‐source project  in Github (https://github.com/emmape/MODifieRProject).  

  • 43.
    Rahman, Aminur
    et al.
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre. The Life Science Center, School of Science and Technology, Örebro University, Sweden.
    Nahar, Noor
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Jass, Jana
    The Life Science Center, School of Science and Technology, Örebro University, Örebro, Sweden.
    Olsson, Björn
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Mandal, Abul
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Complete genome sequence of Lysinibacillus sphaericus B1-CDA: a bacterium that accumulates arsenics2016In: Genome Announcements, ISSN 2169-8287, E-ISSN 2169-8287, Vol. 4, no 1, article id e00999-15Article in journal (Refereed)
    Abstract [en]

    Here, we report the genomic sequence and genetic composition of an arsenic resistant bacterium Lysinibacillus sphaericus B1-CDA. Assembly of the sequencing reads revealed that the genome size is ~4.5 Mb encompassing ~80% of the chromosomal DNA.

  • 44.
    Rahman, Aminur
    et al.
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre. Örebro University.
    Nahar, Noor
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Nawani, Neelu N.
    Dr. D. Y. Patil Biotechnology and Bioinformatics Institute, India.
    Jass, Jana
    Örebro University.
    Ghosh, Sibdas
    Iona College, New Rochelle, NY, USA.
    Olsson, Björn
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Mandal, Abul
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Comparative genome analysis of Lysinibacillus B1-CDA, a bacterium that accumulates arsenics2015In: Genomics, ISSN 0888-7543, E-ISSN 1089-8646, Vol. 106, no 6, p. 384-392Article in journal (Refereed)
    Abstract [en]

    Previously, we reported an arsenic resistant bacterium Lysinibacillus sphaericus B1-CDA, isolated from an arsenic contaminated lands. Here, we have investigated its genetic composition and evolutionary history by using massively parallel sequencing and comparative analysis with other known Lysinibacillus genomes. Assembly of the sequencing reads revealed a genome of ~ 4.5 Mb in size encompassing ~ 80% of the chromosomal DNA. We found that the set of ordered contigs contains abundant regions of similarity with other Lysinibacillus genomes and clearly identifiable genome rearrangements. Furthermore, all genes of B1-CDA that were predicted be involved in its resistance to arsenic and/or other heavy metals were annotated. The presence of arsenic responsive genes was verified by PCR in vitro conditions. The findings of this study highlight the significance of this bacterium in removing arsenics and other toxic metals from the contaminated sources. The genetic mechanisms of the isolate could be used to cope with arsenic toxicity.

  • 45.
    Rahman, Aminur
    et al.
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre. Örebro University.
    Nahar, Noor
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Nawani, Neelu N.
    Dr. D. Y. Patil Biotechnology and Bioinformatics Institute, India.
    Jass, Jana
    Örebro University.
    Ghosh, Sibdas
    Iona College, New Rochelle, NY, USA.
    Olsson, Björn
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Mandal, Abul
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Data in support of the comparative genome analysis of Lysinibacillus B1-CDA, a bacterium that accumulates arsenics2015In: Data in Brief, ISSN 2352-3409, Vol. 5, p. 579-585Article in journal (Refereed)
    Abstract [en]

    This study is a part of our long term project on bioremediation of toxic metals and other pollutants for protection of human health and the environment from severe contamination. The information and results presented in this data article are based on both in vitro and in silico experiments. In vitro experiments were used to investigate the presence of arsenic responsive genes in a bacterial strain B1-CDA that is highly resistant to arsenics. However, in silico studies were used to annotate the function of the metal responsive genes. By using this combined study consisting of in vitro and in silico experiments we have identified and characterized specific genes from B1-CDA that can be used as a potential tool for removal of arsenics as well as other heavy metals from the contaminated environment.

  • 46.
    Rahman, Aminur
    et al.
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Nahar, Noor
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Olsson, Björn
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Mandal, Abul
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Complete Genome Sequence of Enterobacter cloacae B2-DHA: a Chromium-Resistant Bacterium2016In: Genome Announcements, ISSN 2169-8287, E-ISSN 2169-8287, Vol. 4, no 3, article id e00483-16Article in journal (Refereed)
    Abstract [en]

    Previously, we reported a chromium-resistant bacterium, Enterobacter cloacae B2-DHA, isolated from the landfills of tannery industries in Bangladesh. Here, we investigated its genetic composition using massively parallel sequencing and comparative analysis with other known Enterobacter genomes. Assembly of the sequencing reads revealed a genome of ~4.21 Mb in size.

  • 47.
    Rahman, Aminur
    et al.
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre. The Life Science Center, School of Science and Technology, Örebro University, SE-701 82 Örebro, Sweden.
    Olsson, Björn
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Jass, Jana
    The Life Science Center, School of Science and Technology, Örebro University, SE-701 82 Örebro, Sweden.
    Nawani, Neelu
    Microbial Diversity Research Centre, Dr. D.Y. Patil Biotechnology and Bioinformatics Institute, Dr. D. Y. Patil Vidyapeeth, Tathawade, Pune-411033, India.
    Ghosh, Sibdas
    School of Arts and Science, Iona College, New Rochelle, NY 10801, USA.
    Mandal, Abul
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Genome Sequencing Revealed Chromium and Other Heavy Metal Resistance Genes in E. cloacae B2-Dha2017In: Journal of Microbial & Biochemical Technology, E-ISSN 1948-5948, Vol. 9, no 5, p. 191-199Article in journal (Refereed)
    Abstract [en]

    The previously described chromium resistant bacterium, Enterobacter cloacae B2-DHA, was isolated from leather manufacturing tannery landfill in Bangladesh. Here we report the entire genome sequence of this bacterium containing chromium and other heavy metal resistance genes. The genome size and the number of genes, determined by massive parallel sequencing and comparative analysis with other known Enterobacter genomes, are predicted to be 4.22 Mb and 3958, respectively. Nearly 160 of these genes were found to be involved in binding, transport, and catabolism of ions as well as efflux of inorganic and organic compounds. Specifically, the presence of two chromium resistance genes, chrR and chrA was verified by polymerase chain reaction. The outcome of this research highlights the significance of this bacterium in bioremediation of chromium and other toxic metals from the contaminated sources.

  • 48.
    Rao, Aditya
    University of Skövde, School of Humanities and Informatics.
    Tarfetpf: A Plasmodium faciparum protein localization predictor2004Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
  • 49.
    Rao, Aditya
    University of Skövde, School of Humanities and Informatics.
    TargetPf: A Plasmodium falciparum protein localization predictor2004Independent thesis Advanced level (degree of Master (One Year))Student thesis
    Abstract [en]

    Background: In P. falciparum a similarity between the transit peptides of apicoplast and mitochondrial proteins in the context of net positive charge has previously been observed in few proteins. Existing P. falciparum protein localization prediction tools were leveraged in this study to study this similarity in larger sets of these proteins.

    Results: The online public-domain malarial repository PlasmoDB was utilized as the source of apicoplast and mitochondrial protein sequences for the similarity study of the two types of transit peptides. It was found that

    many of the 551 apicoplast-targeted proteins (NEAT proteins) of PlasmoDB may have been wrongly annotated to localize to the apicoplast, as some of these proteins lacked annotations for signal peptides, while others also had annotations for localization to the mitochondrion (NEMT proteins). Also around 50 NEAT proteins could contain signal anchors instead of signal peptides in their N-termini, something that could have an impact on the current theory that explains localization to the apicoplast [1].

    The P. falciparum localization prediction tools were then used to study the similarity in net positive charge between the transit peptides of NEAT and NEMT proteins. It was found that NEAT protein prediction tools like PlasmoAP and PATS could be made to recognize NEMT proteins as NEAT proteins, while the NEMT predicting tool PlasMit could be made to recognize a significant number of NEAT proteins as NEMT. Based on these results a conjecture was proposed that a single technique may be sufficient to predict both apicoplast and mitochondrial transit peptides. An implementation in PERL called TargetPf was implemented to test this conjecture (using PlasmoAP rules), and it reported a total of 408 NEAT

    proteins and 1504 NEMT proteins. This number of predicted NEMT proteins (1504) was significantly higher than the annotated 258 NEMT proteins of plasmoDB, but more in line with the 1200 predictions of the tool PlasMit.

    Conclusions: Some possible ambiguities in the PlasmoDB annotations related to NEAT protein localization were identified in this study. It was also found that existing P. falciparum localization prediction tools can be made to detect transit peptides for which they have not been trained or built for.

  • 50.
    Reddy, Joseph
    University of Skövde, School of Life Sciences.
    Identification and Analysis of Important Proteins in Protein Interaction Networks Using Functional and Topological Information2008Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Studying protein interaction networks using functional and topological information is important for understanding cellular organization and functionality. This study deals with identifying important proteins in protein interaction networks using SWEMODE (Lubovac, et al, 2006) and analyzing topological and functional properties of these proteins with the help of information derived from modular organization in protein interaction networks as well as information available in public resources, in this case, annotation sources describing the functionality of proteins. Multi-modular proteins are short-listed from the modules generated by SWEMODE. Properties of these short-listed proteins are then analyzed using functional information from SGD Gene Ontology(GO) (Dwight, et al., 2002) and MIPS functional categories (Ruepp, et al., 2004). Topological features such as lethality and centrality of these proteins are also investigated, using graph theoretic properties and information on lethal genes from Yeast Hub (Kei-Hoi, et al., 2005). The findings of the study based on GO terms reveal that these important proteins are mostly involved in the biological process of “organelle organization and biogenesis” and a majority of these proteins belong to MIPS “cellular organization” and “transcription” functional categories. A study of lethality reveals that multi-modular proteins are more likely to be lethal than proteins present only in a single module. An examination of centrality (degree of connectivity of proteins) in the network reveals that the ratio of number of important proteins to number of hubs at different hub sizes increases with the hub size (degree).

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