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  • 1.
    Adamovic, Tatjana
    et al.
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Roshani, Leyla
    CMB-Genetics, Göteborg University, SE 40530 Göteborg, Sweden / Department of Clinical Genetics, Göteborg University, SE 40530 Göteborg, Sweden.
    Chen, Lei
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Schaffer, Beverly S.
    Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, United States / Eppley Institute for Research in Cancer, University of Nebraska Medical Center, Omaha, NE 68198, United States.
    Helou, Khalil
    Department of Oncology, Göteborg University, Sahlgrenska University, Göteborg, Sweden.
    Levan, Göran
    CMB-Genetics, Göteborg University, SE 40530 Göteborg, Sweden / Department of Clinical Genetics, Göteborg University, SE 40530 Göteborg, Sweden.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Schull, James D.
    Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, United States / Eppley Institute for Research in Cancer, University of Nebraska Medical Center, Omaha, NE 68198, United States / Department of Genetics, Cell Biology and Anatomy, 6005 Durham Research Center, 985805 Nebraska Medical Center, Omaha, NE 68198-5805, United States.
    Nonrandom pattern of aberrations in 17β-estradiol-induced rat mammary tumors: Indications of distinct pathways for tumor development2007Inngår i: Genes, Chromosomes and Cancer, ISSN 1045-2257, E-ISSN 1098-2264, Vol. 46, nr 5, s. 459-469Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Estrogens play an important role in breast cancer etiology and the ACI rat provides a novel animal model for defining the mechanisms through which estrogens contribute to mammary cancer development. In crossing experiments between the susceptible ACI strain and two resistant strains, COP (Copenhagen) and BN (Brown Norway), several quantitative trait loci (QTL) that affect development of 17b-estradiol (E2)-induced mammary tumors have been defined. Using comparative genomic hybridization (CGH), we have analyzed cytogenetic aberrations in E2-induced mammary cancers and have found clear patterns of nonrandom chromosomal involvement. Approximately two thirds of the tumors exhibited copy number changes. Losses of rat chromosome 5 (RNO5) and RNO20 were particularly common, and it was found that these two aberrations often occurred together. A third recurrent aberration involving proximal gain and distal loss in RNO6 probably defined a distinct subgroup of tumors, since it never occurred in combination with RNO5 loss. Interestingly, QTL with powerful effects on mammary cancer development have been mapped to RNO5 and RNO6. These findings suggest that there were at least two genetic pathways to tumor formation in this rat model of E2-induced mammary cancer. By performing CGH on mammary tumors from ACI rats, F1 rats from crosses between the ACI and COP or BN strains and ACI.BN-Emca8 congenic rats, which carry the BN allele of the Emca8 QTL on RNO5 on the ACI genetic background, we were able to determine that the constitution of the germ line influences the pattern of chromosomal aberrations.

  • 2.
    Andler, Sten F.
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Niklasson, Lars
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Persson, Anne
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Planstedt, Tomas
    Ericsson Microwave Systems AB, Skövde, Sweden.
    De Vin, Leo J.
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Wangler, Benkt
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Ziemke, Tom
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Information Fusion from Databases, Sensors and Simulations: A Collaborative Research Program2005Inngår i: Proceedings: 29th Annual IEEE/NASA Software Engineering Workshop, IEEE Computer Society, 2005, s. 234-241Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper provides an overview of a collaborative research program in information fusion from databases, sensors and simulations. Information fusion entails the combination of data from multiple sources, to generate information that cannot be derived from the individual sources. This area is of strategic importance for industry and defense, as well as public administration areas such as health care, and needs to be pursued as an academic subject. A large number of industrial partners are supporting and participating in the development of the area. The paper describes the program’s general approach and main research areas, with a particular focus on the role of information fusion in systems development

  • 3.
    Berndtsson, Mikael
    et al.
    Högskolan i Skövde, Institutionen för datavetenskap.
    Hansson, J
    Department of Computer and Information Science, Linköping University.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för datavetenskap.
    Lundell, Björn
    Högskolan i Skövde, Institutionen för datavetenskap.
    Planning and implementing your final year project - with success!: a guide for students in computer science and information systems2002Bok (Annet vitenskapelig)
  • 4.
    Berndtsson, Mikael
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Hansson, Jörgen
    Software Engineering Institute, Carnegie Mellon University, Pittsburgh , PA, USA.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Lundell, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Thesis projects: A guide for students in computer science and information systems2008 (oppl. 2)Bok (Annet vitenskapelig)
  • 5. Bräutigam, Marcus
    et al.
    Chawade, Aakash
    Gharti-Chhetri, Gokarna
    Lindlöf, Angelica
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Jonsson, Anders
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Olof
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Jonsson, Rickard
    Development of a Swedish winter oat with gene technology and molecular breeding2006Inngår i: Sveriges utsädesförenings tidskrift, ISSN 0039-6990, Vol. 116, nr 1-2, s. 23-35Artikkel i tidsskrift (Annet vitenskapelig)
  • 6.
    Bräutigam, Marcus
    et al.
    Department of Cell and Molecular Biology, Göteborg University, Box 462, 403 20 Göteborg, Sweden.
    Lindlöf, Angelica
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Zakhrabetkova, Shakhira
    Department of Cell and Molecular Biology, Göteborg University, Box 462, 403 20 Göteborg, Sweden.
    Gharti-Chhetri, Gokarna
    Department of Cell and Molecular Biology, Göteborg University, Box 462, 403 20 Göteborg, Sweden.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Olof
    Department of Cell and Molecular Biology, Göteborg University, Box 462, 403 20 Göteborg, Sweden.
    Generation and analysis of 9792 EST sequences from cold acclimated oat, Avena sativa2005Inngår i: BMC Plant Biology, ISSN 1471-2229, E-ISSN 1471-2229, Vol. 5, s. 18-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background

    Oat is an important crop in North America and northern Europe. In Scandinavia, yields are limited by the fact that oat cannot be used as a winter crop. In order to develop such a crop, more knowledge about mechanisms of cold tolerance in oat is required.

    Results

    From an oat cDNA library 9792 single-pass EST sequences were obtained. The library was prepared from pooled RNA samples isolated from leaves of four-week old Avena sativa (oat) plants incubated at +4°C for 4, 8, 16 and 32 hours. Exclusion of sequences shorter than 100 bp resulted in 8508 high-quality ESTs with a mean length of 710.7 bp. Clustering and assembly identified a set of 2800 different transcripts denoted the Avena sativa cold induced UniGene set (AsCIUniGene set). Taking advantage of various tools and databases, putative functions were assigned to 1620 (58%) of these genes. Of the remaining 1180 unclassified sequences, 427 appeared to be oat-specific since they lacked any significant sequence similarity (Blast E values > 10-10) to any sequence available in the public databases. Of the 2800 UniGene sequences, 398 displayed significant homology (BlastX E values ≤ 10-10) to genes previously reported to be involved in cold stress related processes. 107 novel oat transcription factors were also identified, out of which 51 were similar to genes previously shown to be cold induced. The CBF transcription factors have a major role in regulating cold acclimation. Four oat CBF sequences were found, belonging to the monocot cluster of DREB family ERF/AP2 domain proteins. Finally in the total EST sequence data (5.3 Mbp) approximately 400 potential SSRs were found, a frequency similar to what has previously been identified in Arabidopsis ESTs.

    Conclusion

    The AsCIUniGene set will now be used to fabricate an oat biochip, to perform various expression studies with different oat cultivars incubated at varying temperatures, to generate molecular markers and provide tools for various genetic transformation experiments in oat. This will lead to a better understanding of the cellular biology of this important crop and will open up new ways to improve its agronomical properties.

  • 7.
    Carlsson, Jessica
    et al.
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Davidsson, Sabina
    Orebro Univ Hosp, Dept Urol, Orebro, Sweden / Univ Orebro, Sch Hlth & Med Sci, Orebro, Sweden.
    Helenius, Gisela
    Orebro Univ Hosp, Dept Lab Med, Orebro, Sweden.
    Karlsson, Mats
    Orebro Univ Hosp, Dept Lab Med, Orebro, Sweden.
    Lubovac, Zelmina
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Andren, Ove
    Orebro Univ Hosp, Dept Urol, Orebro, Sweden .
    Olsson, Björn
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Klinga-Levan, Karin
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    A miRNA expression signature that separates between normal and malignant prostate tissues2011Inngår i: Cancer Cell International, ISSN 1475-2867, E-ISSN 1475-2867, Vol. 11, s. 14-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: MicroRNAs (miRNAs) constitute a class of small non-coding RNAs that post-transcriptionally regulate genes involved in several key biological processes and thus are involved in various diseases, including cancer. In this study we aimed to identify a miRNA expression signature that could be used to separate between normal and malignant prostate tissues. Results: Nine miRNAs were found to be differentially expressed (p < 0.00001). With the exception of two samples, this expression signature could be used to separate between the normal and malignant tissues. A cross-validation procedure confirmed the generality of this expression signature. We also identified 16 miRNAs that possibly could be used as a complement to current methods for grading of prostate tumor tissues. Conclusions: We found an expression signature based on nine differentially expressed miRNAs that with high accuracy (85%) could classify the normal and malignant prostate tissues in patients from the Swedish Watchful Waiting cohort. The results show that there are significant differences in miRNA expression between normal and malignant prostate tissue, indicating that these small RNA molecules might be important in the biogenesis of prostate cancer and potentially useful for clinical diagnosis of the disease.

  • 8.
    Carlsson, Jessica
    et al.
    Örebro University / Örebro University Hospital.
    Helenius, Gisela
    Örebro University / Örebro University Hospital.
    Karlsson, Mats G.
    Örebro University / Örebro University Hospital.
    Andrén, Ove
    Örebro University / Örebro University Hospital.
    Klinga-Levan, Karin
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Differences in microRNA expression during tumor development in the transition and peripheral zones of the prostate2013Inngår i: BMC Cancer, ISSN 1471-2407, E-ISSN 1471-2407, Vol. 13, artikkel-id 362Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: The prostate is divided into three glandular zones, the peripheral zone (PZ), the transition zone (TZ), and the central zone. Most prostate tumors arise in the peripheral zone (70-75%) and in the transition zone (20-25%) while only 10% arise in the central zone. The aim of this study was to investigate if differences in miRNA expression could be a possible explanation for the difference in propensity of tumors in the zones of the prostate. Methods: Patients with prostate cancer were included in the study if they had a tumor with Gleason grade 3 in the PZ, the TZ, or both (n=16). Normal prostate tissue was collected from men undergoing cystoprostatectomy (n=20). The expression of 667 unique miRNAs was investigated using TaqMan low density arrays for miRNAs. Student's t-test was used in order to identify differentially expressed miRNAs, followed by hierarchical clustering and principal component analysis (PCA) to study the separation of the tissues. The ADtree algorithm was used to identify markers for classification of tissues and a cross-validation procedure was used to test the generality of the identified miRNA-based classifiers. Results: The t-tests revealed that the major differences in miRNA expression are found between normal and malignant tissues. Hierarchical clustering and PCA based on differentially expressed miRNAs between normal and malignant tissues showed perfect separation between samples, while the corresponding analyses based on differentially expressed miRNAs between the two zones showed several misplaced samples. A classification and cross-validation procedure confirmed these results and several potential miRNA markers were identified. Conclusions: The results of this study indicate that the major differences in the transcription program are those arising during tumor development, rather than during normal tissue development. In addition, tumors arising in the TZ have more unique differentially expressed miRNAs compared to the PZ. The results also indicate that separate miRNA expression signatures for diagnosis might be needed for tumors arising in the different zones. MicroRNA signatures that are specific for PZ and TZ tumors could also lead to more accurate prognoses, since tumors arising in the PZ tend to be more aggressive than tumors arising in the TZ.

  • 9.
    Carlsson, Jessica
    et al.
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Helenius, Gisela
    Örebro University Hospital.
    Karlsson, Mats
    Örebro University Hospital.
    Lubovac, Zelmina
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Andrén, Ove
    Örebro University Hospital.
    Olsson, Björn
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Klinga-Levan, Karin
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Validation of suitable endogenous control genes for expression studies of miRNA in prostate cancer tissues2010Inngår i: Cancer Genetics and Cytogenetics, ISSN 2210-7762, E-ISSN 2210-7770, Vol. 202, nr 2, s. 71-75Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    When performing quantitative polymerase chain reaction analysis, there is a need for correction of technical variation between experiments. This correction is most commonly performed by using endogenous control genes, which are stably expressed across samples, as reference genes for normal expression in a specific tissue. In microRNA (miRNA) studies, two types of control genes are commonly used: small nuclear RNAs and small nucleolar RNAs. In this study, six different endogenous control genes for miRNA studies were investigated in prostate tissue material from the Swedish Watchful Waiting cohort. The stability of the controls was investigated using two different software applications, NormFinder and BestKeeper. RNU24 was the most suitable endogenous control gene for miRNA studies in prostate tissue materials.

  • 10.
    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
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Olof
    Department of Cell and Molecular Biology, Göteborg University, Box 462, 403 20 Göteborg, Sweden.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Putative cold acclimation pathways in Arabidopsis thaliana identified by a combined analysis of mRNA co-expression patterns, promoter motifs and transcription factors2007Inngår i: BMC Genomics, ISSN 1471-2164, E-ISSN 1471-2164, Vol. 8, s. 304-Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 11.
    Chawade, Aakash
    et al.
    CropTailor AB, Lund, Sweden.
    Lindlöf, Angelica
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi. CropTailor AB, Lund, Sweden.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Olsson, Olof
    CropTailor AB, Lund, Sweden / Lund University, Lund, Sweden.
    Global expression profiling of low temperature induced genes in the chilling tolerant japonica rice jumli marshi2013Inngår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 8, nr 12, s. e81729-, artikkel-id e81729Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Low temperature is a key factor that limits growth and productivity of many important agronomical crops worldwide. Rice (Oryza sativa L.) is negatively affected already at temperatures below +10°C and is therefore denoted as chilling sensitive. However, chilling tolerant rice cultivars exist and can be commercially cultivated at altitudes up to 3,050 meters with temperatures reaching as low as +4°C. In this work, the global transcriptional response to cold stress (+4°C) was studied in the Nepalese highland variety Jumli Marshi (spp. japonica) and 4,636 genes were identified as significantly differentially expressed within 24 hours of cold stress. Comparison with previously published microarray data from one chilling tolerant and two sensitive rice cultivars identified 182 genes differentially expressed (DE) upon cold stress in all four rice cultivars and 511 genes DE only in the chilling tolerant rice. Promoter analysis of the 182 genes suggests a complex cross-talk between ABRE and CBF regulons. Promoter analysis of the 511 genes identified over-represented ABRE motifs but not DRE motifs, suggesting a role for ABA signaling in cold tolerance. Moreover, 2,101 genes were DE in Jumli Marshi alone. By chromosomal localization analysis, 473 of these cold responsive genes were located within 13 different QTLs previously identified as cold associated.

  • 12.
    Chen, Lei
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Nordlander, Carola
    CMB-Genetics, Lundberg Laboratory, Göteborg University, Göteborg, Sweden.
    Behboudi, Afrouz
    CMB-Genetics, Lundberg Laboratory, Göteborg University, Göteborg, Sweden.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Klinga Levan, Karin
    Högskolan i Skövde, Institutionen för vård och natur.
    Deriving evolutionary tree models of the oncogenesis of endometrial adenocarcinoma2007Inngår i: International Journal of Cancer, ISSN 0020-7136, E-ISSN 1097-0215, Vol. 120, nr 2, s. 292-296Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Endometrial adenocarcinoma (EAC) is the fourth leading cause of cancer death in women worldwide, but not much is known about the underlying genetic factors involved in the development of this complex disease. In the present work, we used 3 different algorithms to derive tree models of EAC oncogenesis from data on the frequencies of genomic alterations in rat chromosome 10 (RNO10). The tumor material was derived from progenies of crosses between the EAC susceptible BDII inbred rat strain and two non susceptible inbred rat strains. Data from allelic imbalance scans of RNO10 with microsatellite markers on solid tumor material and corresponding tissue cultures were used. For the analysis, RNO10 was divided into 24 segments containing a total of 59 informative microsatellite markers. The derived tree models show that genomic alterations have occurred in 11 of the 24 segments. In addition, the models provide information about the likely order of the alterations as well as their relationship with each other. Interestingly, there was a high degree of consistency among the different tree models and with the results of previous-studies, which supports the reliability of the tree models. Our results may be extended into a general approach for tree modeling of whole genome alterations during oncogenesis. (c) 2006 Wiley-Liss, Inc.

  • 13. Dura, Elzbieta
    et al.
    Gawronska, Barbara
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Erlendsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Towards Information Fusion in Pathway Evaluation: Encoding Relations in Biomedical Texts2006Inngår i: The 9th International Conference on Information Fusion: Florence, Italy, 10-13 July 2006, IEEE Press, 2006, s. 240-247Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    The long-term goal of the research presented in this paper is to incorporate linguistic text analysis into a system for evaluation of biological pathways. In this system, relations extracted from biomedical texts will be compared with pathways encoded in existing specialized databases. In this way, the biologist's conclusions regarding the plausibility and/or novelty of a certain relation between genes, proteins, etc., can be supported by fused information from biological databases and biological literature. We aim at overcoming the shortcomings of existing systems for information retrieval by proposing a method based on thorough linguistic analysis of a large text corpus. In this paper, we present a comparative analysis of two corpora: one consisting of biomedical texts from PubMed, the other one of general English prose. The results stress the importance of taking multiword entries into account when constructing a system for extracting biological relations from texts

  • 14.
    Eriksson, Roger
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Adapting Genetic Regulatory Models by Genetic Programming2004Inngår i: Biosystems (Amsterdam. Print), ISSN 0303-2647, E-ISSN 1872-8324, Vol. 76, nr 1-3, s. 217-227Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper, we focus on the task of adapting genetic regulatory models based on gene expression data from microarrays. Our approach aims at automatic revision of qualitative regulatory models to improve their fit to expression data. We describe a type of regulatory model designed for this purpose, a method for predicting the quality of such models, and a method for adapting the models by means of genetic programming. We also report experimental results highlighting the ability of the methods to infer models on a number of artificial data sets. In closing, we contrast our results with those of alternative methods, after which we give some suggestions for future work.

  • 15.
    Eriksson, Roger
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    On the Performance of Evolutionary Algorithms with LifeTime Adaptation in Dynamic Fitness Landscapes2004Inngår i: 2004 IEEE Congress on Evolutionary Computation, 2004, s. 1286-1292Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    Dynamic optimisation problems are becoming increasingly important; meanwhile, progress in optimisation techniques and in computational resources are permitting the development of effective systems for dynamic optimisation, resulting in a need for objective methods to evaluate and compare different techniques. The search for effective techniques may be seen as a multi-objective problem, trading off time complexity against effectiveness; hence benchmarks must be able to compare techniques across the Pareto front, not merely at a single point. We propose benchmarks for the dynamic travelling salesman problem, adapted from the CHN-144 benchmark of 144 Chinese cities for the static travelling salesman problem. We provide an example of the use of the benchmark, and illustrate the information that can be gleaned from analysis of the algorithm performance on

  • 16.
    Fagerlind, Magnus
    et al.
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för biovetenskap.
    Stålhammar, Hans
    VikingGenetics, Skara.
    Olsson, Björn
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för biovetenskap.
    Klinga-Levan, Karin
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för biovetenskap.
    Expression of miRNAs in Bull Spermatozoa Correlates with Fertility Rates2015Inngår i: Reproduction in domestic animals, ISSN 0936-6768, E-ISSN 1439-0531, Vol. 50, nr 4, s. 587-594Artikkel i tidsskrift (Fagfellevurdert)
  • 17.
    Gamalielson, Jonas
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    On the Robustness of Algorithms for Clustering of Gene Expression Data2003Rapport (Annet vitenskapelig)
    Abstract [en]

    The progress in microarray technology is evident and huge amounts of gene expression data are currently being produced. A complicating matter is that there are various sources of uncertainty in microarray experiments, as well as in the analysis of expression data. This problem has generated an increased interest in the validation of methods for analysis of expression data. Clustering algorithms have been found particularly useful for the study of coexpressed genes, and this paper therefore concerns the robustness of partitional clustering algorithms. These algorithms use a predefined number of clusters and assign each gene to exactly one cluster. The effect of repeated clustering using identical algorithm parameters and input data is investigated for the self-organizing map (SOM) and the $k$-means algorithm. The susceptibility to measurement noise is also studied. A reproducibility measure is proposed and used to assess the results from the performed clustering experiments. Well-known publicly available datasets are used. Results show that clusterings are not necessarily reproducible even when identical algorithm parameters are used, and that the problems are aggravated when measurement noise is introduced.

  • 18.
    Gamalielsson, Jonas
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Nilsson, Patric
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    A GO-based Method for Assessing the Biological Plausibility of Regulatory Hypotheses2006Inngår i: ICCS 2006: 6th International Conference on Computational Science, 2006, s. 879-886Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    Many algorithms have been proposed for deriving regulatory networks from microarray gene expression data. The performance of such algorithms is often measured by how well the resulting network can recreate the gene expression data that it was derived from. However, this kind of performance does not necessarily mean that the regulatory hypotheses in the network are biologically plausible. We therefore propose a method for assessing the biological plausibility of regulatory hypotheses using prior knowledge in the form of regulatory pathway databases and Gene Ontology-based annotation of gene products. A set of templates is derived by generalising from known interactions to typical properties of interacting gene product pairs. By searching for matches in this set of templates, the plausibility of regulatory hypotheses can be assessed. We evaluate to what degree the collection of templates can separate true from false positive interactions, and we illustrate the practical use of the method by applying it to an example network reconstruction problem.

  • 19.
    Gamalielsson, Jonas
    et al.
    Högskolan i Skövde, Institutionen för vård och natur.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för vård och natur.
    EGOSAP: Evolutionary Gene Ontology based Semantic Alignment of Biological Pathways2007Inngår i: Proceedings of the third Moscow Conference on Computational Molecular Biology, Moscow, Russia, 27-30 July 2007, 2007, s. 98-100Konferansepaper (Fagfellevurdert)
  • 20.
    Gamalielsson, Jonas
    et al.
    Högskolan i Skövde, Institutionen för datavetenskap.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för vård och natur.
    Evaluating Protein Structure Prediction Models with Evolutionary Algorithms2005Inngår i: Information processing with evolutionary algorithms: from industrial applications to academic speculations / [ed] Manuel Graña, Richard Duro, Alicia d’Anjou and Paul P. Wang, Springer London, 2005, s. 143-158Kapittel i bok, del av antologi (Fagfellevurdert)
  • 21.
    Gamalielsson, Jonas
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Gene Ontology-based Semantic Alignment of Biological Pathways by Evolutionary Search2008Inngår i: Journal of Bioinformatics and Computational Biology, ISSN 0219-7200, E-ISSN 1757-6334, Vol. 6, nr 4, s. 825-842Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 22.
    Gamalielsson, Jonas
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    GOSAP: Gene Ontology based Semantic Alignment of Biological Pathways2008Inngår i: International Journal of Bioinformatics Research and Applications, ISSN 1744-5485, E-ISSN 1744-5493, Vol. 4, nr 3, s. 274-294Artikkel i tidsskrift (Fagfellevurdert)
  • 23.
    Gamalielsson, Jonas
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    GOSAP: Gene Ontology Based Semantic Alignment of Biological Pathways2005Rapport (Annet vitenskapelig)
    Abstract [en]

    A large number of biological pathways have been assembled in later years, and are being stored in databases. Hence, the need for methods to analyse these pathways has emerged. One class of methods compares pathways, in order to discover parts that are evolutionary conserved between species or to discover intra-species similarites. Most previous work has been focused on methods targeted at metabolic pathways utilising the EC enzyme hierarchy. Here, we propose a Gene Ontology (GO) based approach for finding semantic local alignments when comparing paths in biological pathways where the nodes are gene products. The method takes advantage of all three sub-ontologies, and uses a measure of semantic similarity to calculate a match score between gene products. Our proposed method is applicable to all types of biological pathways, where nodes are gene products, e.g. regulatory pathways, signalling pathways and metabolic enzyme-to-enzyme pathways. It would also be possible to extend the method to work with other types of nodes, as long as there is an ontology or abstraction hierarchy available for categorising the nodes. We demonstrate that the method is useful for studying protein regulatory pathways in S. cerevisiae, as well as metabolic pathways for the same organism.

  • 24.
    Gamalielsson, Jonas
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för kommunikation och information.
    On the (lack of) robustness of gene expression data clustering2004Inngår i: WSEAS Transactions on Biology and Biomedicine, ISSN 1109-9518, E-ISSN 2224-2902, Vol. 1, nr 2, s. 198-204Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 25.
    Gamalielsson, Jonas
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Nilsson, Patric
    Högskolan i Skövde, Institutionen för kommunikation och information.
    A Gene Ontology based Method for Assessing the Biological Plausibility of Regulatory Hypotheses2005Rapport (Annet vitenskapelig)
    Abstract [en]

    Many algorithms that derive gene regulatory networks from microarray gene expression data have been proposed in the literature. The performance of such an algorithm is often measured by how well a genetic network can recreate the gene expression data that the network was derived from. However, this kind of performance does not necessarily mean that the regulatory hypotheses in the network are biologically plausible. We therefore propose a Gene Ontology based method for assessing the biological plausibility of regulatory hypotheses at the gene product level using prior biological knowledge in the form of Gene Ontology annotation of gene products and regulatory pathway databases. Templates are designed to encode general knowledge, derived by generalizing from known interactions to typical properties of interacting gene product pairs. By matching regulatory hypotheses to templates, the plausible hypotheses can be separated from inplausible ones. In a cross-validation test we verify that the templates reliably identify interactions which have not been used in the template creation process, thereby confirming the generality of the approach. The method also proves useful when applied to an example network reconstruction problem, where a Bayesian approach is used to create hypothetical relations which are evaluated for biological plausibility. The cell cycle pathway and the MAPK signaling pathway for S. cerevisiae and H. sapiens are used in the experiments.

  • 26.
    Gawronska, Barbara
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Erlendsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Tracking biological relations in texts: a Referent Grammar based approach2005Inngår i: Proceedings of the workshop Biomedical Ontologies and Text Processing, in connection to ECCB/05: 4th European Conference on Computational Biology, 2005, s. 15-22Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, we describe a method for extracting biological relations (in the first place, relations used in the KEGG ontology of biological pathways) from scientific texts. The main assumption is that correct syntactic analysis combined with domain-specific heuristics provides a good basis for relation extraction. We propose an algorithm that searches through the syntactic trees produced by a parser based on a formalism called Referent Grammar (inspired by Categorial Grammar), identifies relations mentioned in the sentence, and classifies them with respect to their semantic class and epistemic status (facts, counterfactuals, hypotheses).

  • 27.
    Gawronska, Barbara
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    De Vin, Leo
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Natural Language Technology In Multi-Source Information Fusion2004Inngår i: Proceedings of the International IPSI-2004k Conference, 2004Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Information Fusion encompasses "the theory, techniques and tools conceived for exploiting the synergy in the information acquired from multiple sources" [http://www.inforfusion.org/mission.htm]. The main issue is to improve the quality of decisions utilizing several information sources (databases, sensors, simulations). Research on information fusion has focused on applications like robotics and command and control systems, but the need of information synergy concerns more and more fields. Natural language serves as important information source in all areas of human activity, but the integration of language into fusion systems is far from satisfactory. The paper discusses employing language technology in bioinformatics, and in industrial processes.

  • 28.
    Gawronska, Barbara
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Erlendsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Towards an Automated Analysis of Biomedical Abstracts2006Inngår i: Data Integration in the Life Sciences: Third International Workshop, DILS 2006, Springer, 2006, s. 50-65Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    An essential part of bioinformatic research concerns the iterative process of validating hypotheses by analyzing facts stored in databases and in published literature. This process can be enhanced by language technology methods, in particular by automatic text understanding. Since it is becoming increasingly difficult to keep up with the vast number of scientific articles being published, there is a need for more easily accessible representations of the current knowledge. The goal of the research described in this paper is to develop a system aimed to support the large-scale research on metabolic and regulatory pathways by extracting relations between biological objects from descriptions found in literature. We present and evaluate the procedures for semantico-syntactic tagging, dividing the text into parts concerning previous research and current research, syntactic parsing, and transformation of syntactic trees into logical representations similar to the pathway graphs utilized in the Kyoto Encyclopaedia of Genes and Genomes.

  • 29.
    Ghosheh, Nidal
    et al.
    Högskolan i Skövde, Institutionen för biovetenskap. Högskolan i Skövde, Forskningscentrum för Systembiologi. Institute of Biomedicine, Department of Clinical Chemistry and Transfusion Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för biovetenskap. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Edsbagge, Josefina
    Takara Bio Europe AB, Gothenburg, Sweden.
    Küppers-Munther, Barbara
    Takara Bio Europe AB, Gothenburg, Sweden.
    Van Giezen, Mariska
    Takara Bio Europe AB, Gothenburg, Sweden.
    Asplund, Annika
    Högskolan i Skövde, Institutionen för biovetenskap. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Andersson, Tommy B.
    AstraZeneca R&D, CVMD DMPK, Mölndal, Sweden / Department of Physiology and Pharmacology, Section of Pharmacogenetics, Karolinska Institutet, Stockholm, Sweden.
    Björquist, Petter
    NovaHep AB, Gothenburg, Sweden.
    Carén, Helena
    Sahlgrenska Cancer Center, Department of Pathology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    Simonsson, Stina
    Institute of Biomedicine, Department of Clinical Chemistry and Transfusion Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    Sartipy, Peter
    Högskolan i Skövde, Institutionen för biovetenskap. Högskolan i Skövde, Forskningscentrum för Systembiologi. AstraZeneca R&D, GMD CVMD GMed, Mölndal, Sweden.
    Synnergren, Jane
    Högskolan i Skövde, Institutionen för biovetenskap. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Highly Synchronized Expression of Lineage-Specific Genes during In Vitro Hepatic Differentiation of Human Pluripotent Stem Cell Lines2016Inngår i: Stem Cells International, ISSN 1687-9678, Vol. 2016, artikkel-id 8648356Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Human pluripotent stem cells- (hPSCs-) derived hepatocytes have the potential to replace many hepatic models in drug discovery and provide a cell source for regenerative medicine applications. However, the generation of fully functional hPSC-derived hepatocytes is still a challenge. Towards gaining better understanding of the differentiation and maturation process, we employed a standardized protocol to differentiate six hPSC lines into hepatocytes and investigated the synchronicity of the hPSC lines by applying RT-qPCR to assess the expression of lineage-specific genes (OCT4, NANOG, T, SOX17, CXCR4, CER1, HHEX, TBX3, PROX1, HNF6, AFP, HNF4a, KRT18, ALB, AAT, and CYP3A4) which serve as markers for different stages during liver development. The data was evaluated using correlation and clustering analysis, demonstrating that the expression of these markers is highly synchronized and correlated well across all cell lines. The analysis also revealed a distribution of the markers in groups reflecting the developmental stages of hepatocytes. Functional analysis of the differentiated cells further confirmed their hepatic phenotype. Taken together, these results demonstrate, on the molecular level, the highly synchronized differentiation pattern across multiple hPSC lines. Moreover, this study provides additional understanding for future efforts to improve the functionality of hPSC-derived hepatocytes and thereby increase the value of related models.

  • 30.
    Jurcevic, Sanja
    et al.
    Högskolan i Skövde, Institutionen för biovetenskap. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Klinga-Levan, Karin
    Högskolan i Skövde, Institutionen för biovetenskap. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för biovetenskap. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Ejeskär, Katarina
    Högskolan i Skövde, Institutionen för biovetenskap. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Verification of microRNA expression in human endometrial adenocarcinoma2016Inngår i: BMC Cancer, ISSN 1471-2407, E-ISSN 1471-2407, Vol. 16, nr 1, artikkel-id 261Artikkel i tidsskrift (Fagfellevurdert)
  • 31.
    Jurcevic, Sanja
    et al.
    Högskolan i Skövde, Institutionen för biovetenskap. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Olsson, Björn
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för biovetenskap.
    Klinga-Levan, Karin
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för biovetenskap.
    MicroRNA expression in human endometrial adenocarcinoma2014Inngår i: Cancer Cell International, ISSN 1475-2867, E-ISSN 1475-2867, Vol. 14, nr 1, artikkel-id 88Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    BACKGROUND: MicroRNAs are small non-coding RNAs that play crucial roles in the pathogenesis of different cancer types. The aim of this study was to identify miRNAs that are differentially expressed in endometrial adenocarcinoma compared to healthy endometrium. These miRNAs can potentially be used to develop a panel for classification and prognosis in order to better predict the progression of the disease and facilitate the choice of treatment strategy.

    METHODS: Formalin fixed paraffin embedded endometrial tissue samples were collected from the Örebro university hospital. QPCR was used to quantify the expression levels of 742 miRNAs in 30 malignant and 20 normal endometrium samples. After normalization of the qPCR data, miRNAs differing significantly in expression between normal and cancer samples were identified, and hierarchical clustering analysis was used to identify groups of miRNAs with coordinated expression profiles.

    RESULTS: In comparisons between endometrial adenocarcinoma and normal endometrium samples 138 miRNAs were found to be significantly differentially expressed (p < 0.001) among which 112 miRNAs have not been previous reported for endometrial adenocarcinoma.

    CONCLUSION: Our study shows that several miRNAs are differentially expressed in endometrial adenocarcinoma. These identified miRNA hold great potential as target for classification and prognosis of this disease. Further analysis of the differentially expressed miRNA and their target genes will help to derive new biomarkers that can be used for classification and prognosis of endometrial adenocarcinoma.

  • 32.
    Jurcevic, Sanja
    et al.
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Klinga-Levan, Karin
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Validation of Suitable Endogenous Control Genes for Quantitative PCR Analysis of microRNA gene expression in a rat model of endometrial cancer2013Inngår i: Cancer Cell International, ISSN 1475-2867, E-ISSN 1475-2867, Vol. 13, artikkel-id 45Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background

    MicroRNAs are small RNA molecules that negatively regulate gene expression by translational inhibition or mRNA cleavage. The discovery that abnormal expression of particular miRNAs contributes to human disease, including cancer, has spurred growing interest in analysing expression profiles of these molecules. Quantitative polymerase chain reaction is frequently used for quantification of miRNA expression due to its sensitivity and specificity. To minimize experimental error in this system an appropriate endogenous control gene must be chosen. An ideal endogenous control gene should be expressed at a constant level across all samples and its expression stability should be unaffected by the experimental procedure.

    Results

    The expression and validation of candidate control genes (4.5S RNA(H) A, Y1, 4.5S RNA(H) B, snoRNA, U87 and U6) was examined in 21 rat cell lines to establish the most suitable endogenous control for miRNA analysis in a rat model of cancer. The stability of these genes was analysed using geNorm and NormFinder algorithms. U87 and snoRNA were identified as the most stable control genes, while Y1 was least stable.

    Conclusion

    This study identified the control gene that is most suitable for normalizing the miRNA expression data in rat. That reference gene will be useful when miRNAs expression are analyzed in order to find new miRNA markers for endometrial cancer in rat.

  • 33.
    Kariminejad, Ariana
    et al.
    Kariminejad-Najmabadi Pathology & Genetics Centre, Tehran, Iran.
    Almadani, Navid
    Kariminejad-Najmabadi Pathology & Genetics Centre, Tehran, Iran.
    Khoshaeen, Atefeh
    Mehrgan Genetics Centre, Sari, Iran.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för biovetenskap. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Moslemi, Ali-Reza
    Department of Pathology, University of Gothenburg, Sahlgrenska University Hospital, Gothenburg, Sweden.
    Tajsharghi, Homa
    Högskolan i Skövde, Institutionen för biovetenskap. Högskolan i Skövde, Forskningscentrum för Systembiologi. Department of Pathology, University of Gothenburg, Sahlgrenska University Hospital, Gothenburg, Sweden.
    Truncating CHRNG mutations associated with interfamilial variability of the severity of the Escobar variant of multiple pterygium syndrome2016Inngår i: BMC Genetics, ISSN 1471-2156, E-ISSN 1471-2156, Vol. 17, nr 1, artikkel-id 71Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    BACKGROUND:In humans, muscle-specific nicotinergic acetylcholine receptor (AChR) is a transmembrane protein with five different subunits, coded by CHRNA1, CHRNB, CHRND and CHRNG/CHRNE. The gamma subunit of AChR encoded by CHRNG is expressed during early foetal development, whereas in the adult, the γ subunit is replaced by a ε subunit. Mutations in the CHRNG encoding the embryonal acetylcholine receptor may cause the non-lethal Escobar variant (EVMPS) and lethal form (LMPS) of multiple pterygium syndrome. The MPS is a condition characterised by prenatal growth failure with pterygium and akinesia leading to muscle weakness and severe congenital contractures, as well as scoliosis.

    RESULTS:Our whole exome sequencing studies have identified one novel and two previously reported homozygous mutations in CHRNG in three families affected by non-lethal EVMPS. The mutations consist of deletion of two nucleotides, cause a frameshift predicted to result in premature termination of the foetally expressed gamma subunit of the AChR.

    CONCLUSIONS:Our data suggest that severity of the phenotype varies significantly both within and between families with MPS and that there is no apparent correlation between mutation position and clinical phenotype. Although individuals with CHRNG mutations can survive, there is an increased frequency of abortions and stillbirth in their families. Furthermore, genetic background and environmental modifiers might be of significance for decisiveness of the lethal spectrum, rather than the state of the mutation per se. Detailed clinical examination of our patients further indicates the changing phenotype from infancy to childhood.

  • 34.
    Karlsson, Elin
    et al.
    Department of Oncology, Institute of Clinical Sciences, Göteborg University, Blå stråket 2, SE-413 45 Göteborg, Sweden.
    Danielsson, Anna
    Department of Oncology, Institute of Clinical Sciences, Göteborg University, Blå stråket 2, SE-413 45 Göteborg, Sweden.
    Delle, Ulla
    Department of Oncology, Institute of Clinical Sciences, Göteborg University, Blå stråket 2, SE-413 45 Göteborg, Sweden.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Karlsson, Per
    Oncology Section, Department of Oncology, Sahlgrenska University Hospital, Blå stråket 2, SE-413 45 Göteborg, Sweden.
    Helou, Khalil
    Department of Oncology, Institute of Clinical Sciences, Göteborg University, Blå stråket 2, SE-413 45 Göteborg, Sweden.
    Chromosomal changes associated with clinical outcome in lymph node-negative breast cancer2007Inngår i: Cancer Genetics and Cytogenetics, ISSN 2210-7762, E-ISSN 2210-7770, Vol. 172, nr 2, s. 139-146Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Breast cancer is the most common malignancy among women and accounts for over one million new cases worldwide per year. Lymph node-negative breast cancer patients are reputed as having a better prognosis than lymph node-positive ones. Around 20% of the lymph node-negative patients die within 10 years after diagnosis. To improve the prognostics of node-negative breast cancer, it is important to understand the underlying biologic mechanisms promoting survival, such as specific genetic changes in the tumor genome. In this study, CGH was applied to analyze 64 tumors from node-negative breast cancer patients to identify DNA copy number changes in chromosomes and chromosome regions that may be correlated to survival. The main findings show gains at 4q, 5q31not, vert, similarqter, 6q12not, vert, similarq16, and 12q14not, vert, similarq22, as well as losses of 17p, 18p, and Xq, which were significantly more recurrent in tumors from deceased patients than in tumors from survivors. The average number of chromosomal changes was higher in the tumors from deceased compared to the survivor tumors. Our findings suggest that tumors with specific chromosomal aberrations at 4q, 5q31not, vert, similarqter, 6q12not, vert, similarq16, 12q14not, vert, similarq22, 17p, 18p, and Xq result in an aggressive form of breast cancer and that these patients are predisposed to succumb to breast cancer.

  • 35.
    Karlsson, Elin
    et al.
    Univ Gothenburg, Inst Clin Sci, Dept Oncol, SE-41345 Gothenburg, Sweden.
    Delle, Ulla
    Univ Gothenburg, Inst Clin Sci, Dept Oncol, SE-41345 Gothenburg, Sweden.
    Danielsson, Anna
    Univ Gothenburg, Inst Clin Sci, Dept Oncol, SE-41345 Gothenburg, Sweden.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för vård och natur.
    Abel, Frida
    Genom Core Facil, SE-40530 Gothenburg, Sweden.
    Karlsson, Per
    Univ Gothenburg, Sahlgrenska Univ Hosp, Dept Oncol, Oncol Sect, SE-41345 Gothenburg, Sweden.
    Helou, Khalil
    Univ Gothenburg, Inst Clin Sci, Dept Oncol, SE-41345 Gothenburg, Sweden.
    Gene expression variation to predict 10-year survival in lymph-node-negative breast cancer2008Inngår i: BMC Cancer, ISSN 1471-2407, E-ISSN 1471-2407, Vol. 8, s. 254-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: It is of great significance to find better markers to correctly distinguish between high-risk and low-risk breast cancer patients since the majority of breast cancer cases are at present being overtreated. Methods: 46 tumours from node-negative breast cancer patients were studied with gene expression microarrays. A t-test was carried out in order to find a set of genes where the expression might predict clinical outcome. Two classifiers were used for evaluation of the gene lists, a correlation-based classifier and a Voting Features Interval (VFI) classifier. We then evaluated the predictive accuracy of this expression signature on tumour sets from two similar studies on lymph-node negative patients. They had both developed gene expression signatures superior to current methods in classifying node-negative breast tumours. These two signatures were also tested on our material. Results: A list of 51 genes whose expression profiles could predict clinical outcome with high accuracy in our material (96% or 89% accuracy in cross-validation, depending on type of classifier) was developed. When tested on two independent data sets, the expression signature based on the 51 identified genes had good predictive qualities in one of the data sets (74% accuracy), whereas their predictive value on the other data set were poor, presumably due to the fact that only 23 of the 51 genes were found in that material. We also found that previously developed expression signatures could predict clinical outcome well to moderately well in our material (72% and 61%, respectively). Conclusion: The list of 51 genes derived in this study might have potential for clinical utility as a prognostic gene set, and may include candidate genes of potential relevance for clinical outcome in breast cancer. According to the predictions by this expression signature, 30 of the 46 patients may have benefited from different adjuvant treatment than they recieved. Trial registration: The research on these tumours was approved by the Medical Faculty Research Ethics Committee (Medicinska fakultetens forskningsetikkommitte, Goteborg, Sweden (S164-02)).

  • 36.
    Karlsson, Sandra
    et al.
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Olsson, Björn
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Klinga-Levan, Karin
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Gene expression profiling predicts a three-gene expression signature of endometrial adenocarcinoma in a rat model2009Inngår i: Cancer Cell International, ISSN 1475-2867, E-ISSN 1475-2867, Vol. 9, s. Article Number: 12-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

     

    Background: In the Western world, endometrial cancers are the most common gynaecological neoplastic disorders among women. Initial symptoms are often vague and may be confused with several other conditions or disorders. Thus, there is a need for an easy and reliable diagnostic tool. The objective of this work was to identify a gene expression signature specific for endometrial adenocarcinomas to be used for testing potential endometrial biomarkers.

    Results: Changes in expression between endometrial adenocarcinomas and non-/pre-malignant endometrium from the BDII EAC rat model were compared in cDNA microarray assays. By employing classification analysis (Weka) on the expression data from approximately 5600 cDNA clones and TDT analysis on genotype data, we identified a three-gene signature (Gpx3, Bgn and Tgfb3). An independent analysis of differential expression, revealed a total of 354 cDNA clones with significant changes in expression. Among the 10 best ranked clones, Gpx3, Bgn and Tgfb3 were found.

     

    Conclusion: Taken together, we present a unique data set of genes with different expression patterns between EACs and non-/pre-malignant endometrium, and specifically we found three genes that were confirmed in two independent analyses. These three genes are candidates for an EAC signature and further evaluations of their involvement in EAC tumorigenesis will be undertaken.

  • 37.
    Laurio, Kim
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Svensson, Thomas
    Biovitrum AB, Göteborg, Sweden.
    Jirstrand, Mats
    Fraunhofer-Chalmers Research Center for Industrial Mathematics, Göteborg, Sweden.
    Nilsson, Patric
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Gamalielsson, Jonas
    Högskolan i Skövde, Institutionen för kommunikation och information. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Evolutionary search for improved path diagrams2007Inngår i: Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics: 5th European Conference, EvoBIO 2007, Valencia, Spain, April 11-13, 2007. Proceedings / [ed] Elena Marchiori, Jason H. Moore, Jagath C. Rajapakse, Springer Berlin/Heidelberg, 2007, s. 114-121Konferansepaper (Fagfellevurdert)
    Abstract [en]

    A path diagram relates observed, pairwise, variable correlations to a functional structure which describes the hypothesized causal relations between the variables. Here we combine path diagrams, heuristics and evolutionary search into a system which seeks to improve existing gene regulatory models. Our evaluation shows that once a correct model has been identified it receives a lower prediction error compared to incorrect models, indicating the overall feasibility of this approach. However, with smaller samples the observed correlations gradually become more misleading, and the evolutionary search increasingly converges on suboptimal models. Future work will incorporate publicly available sources of experimentally verified biological facts to computationally suggest model modifications which might improve the model’s fitness.

  • 38.
    Levan, Kristina
    et al.
    University of Gothenburg.
    Partheen, Karolina
    University of Gothenburg.
    Österberg, Lovisa
    University of Gothenburg.
    Olsson, Björn
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Delle, Ulla
    University of Gothenburg.
    Eklind, Saskia
    University of Gothenburg.
    Horvath, György
    University of Gothenburg.
    Identification of a Gene Expression Signature for Survival Prediction in Type I Endometrial Carcinoma2010Inngår i: Gene Expression, ISSN 1052-2166, E-ISSN 1555-3884, Vol. 14, nr 6, s. 361-370Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Endometrial cancer is the most common malignancy of the female reproductive tract. In many cases the prognosis is favorable, but 22% of affected women die from the disease. We aimed to study potential differences in gene expression between endometrioid adenocarcinomas from survivors (5-year survival) and nonsurvivors. Forty-five patients were included in the investigation, of which 21 were survivors and 24 were nonsurvivors. The tumors were analyzed with genome-wide expression array analysis, represented by 13,526 genes. Distinct differences in gene expression were found between the groups. A t-test established that 218 genes were significantly differentially expressed (p < 0.001) between the two survival groups, and in a cross-validation test 40 of the 45 (89%) tumors were classified correctly. The 218 differentially expressed genes were subjected to hierachical clustering analysis, which yielded two clusters both exhibiting over 80% homogeneity with respect to survival. When the additional constraint of fold change (FC > 2) was added the hierachical clustering yielded similar results. Stage I tumors are expected to have a favorable prognosis. However, in our tumor material there were six nonsurvivors with stage I tumors. Five out of six stage I nonsurvivors clustered in the nonsurvival fraction. Our findings suggest that a subgroup of early stage endometroid adenocarcinomas can be correctly classified as potentially aggressive by using molecular biology in combination with conventional markers, thereby providing a tool for a more accurate classification and risk evaluation of the individual patient.

  • 39.
    Linde, Jörg
    et al.
    Leibniz-Institute for Natural Product Research and Infection Biology.
    Olsson, Björn
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Lubovac, Zelmina
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Network Properties for Ranking Predicted miRNA Targets in Breast Cancer2009Inngår i: Advances in Bioinformatics, ISSN 1687-8027, E-ISSN 1687-8035, s. Article ID 182689-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    MicroRNAs control the expression of their target genes by translational repression and transcriptional cleavage. They are involved in various biological processes including development and progression of cancer. To uncover the biological role of miRNAs it is important to identify their target genes. The small number of experimentally validated target genes makes computer prediction methods very important. However, state-of-the-art prediction tools result in a great number of putative targets with an unpredictable number of false positives. In this paper, we propose and evaluate two approaches for ranking the biological relevance of putative targets of miRNAs which are associated with breast cancer.

  • 40.
    Lindlöf, Angelica
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Bräutigam, Marcus
    Chawade, Aakash
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Olof
    Identification of Cold-Induced Genes in Cereal Crops and Arabidopsis through Comparative Analysis of Multiple EST sets2007Inngår i: Bioinformatics Research and Development: First International Conference, Springer Berlin/Heidelberg, 2007, s. 48-65Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Freezing tolerance in plants is obtained during a period of low non-freezing temperatures before the winter sets on, through a biological process known as cold acclimation. Cold is one of the major stress factors that limits the growth, productivity and distribution of plants, and understanding the mechanism of cold tolerance is therefore important for crop improvement. Expressed sequence tags (EST) analysis is a powerful, economical and time-efficient way of assembling information on the transcriptome. To date, several EST sets have been generated from cold-induced cDNA libraries from several different plant species. In this study we utilize the variation in the frequency of ESTs sampled from different cold-stressed plant libraries, in order to identify genes preferentially expressed in cold in comparison to a number of control sets. The species included in the comparative study are oat (Avena sativa), barley (Hordeum vulgare), wheat (Triticum aestivum), rice (Oryza sativa) and Arabidopsis thaliana. However, in order to get comparable gene expression estimates across multiple species and data sets, we choose to compare the expression of tentative ortholog groups (TOGs) instead of single genes, as in the normal procedure. We consider TOGs as preferentially expressed if they are detected as differentially expressed by a test statistic and up-regulated in comparison to all control sets, and/or uniquely expressed during cold stress, i.e., not present in any of the control sets. The result of this analysis revealed a diverse representation of genes in the different species. In addition, the derived TOGs mainly represent genes that are long-term highly or moderately expressed in response to cold and/or other stresses.

  • 41.
    Lindlöf, Angelica
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Bräutigam, Marcus
    Göteborg University.
    Chawade, Aakash
    Göteborg University.
    Olsson, Olof
    Göteborg University.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information. Högskolan i Skövde, Forskningscentrum för Systembiologi. Bioinformatik, Bioinformatics.
    Evaluation of combining several statistical methods with a flexible cutoff for identifying differentially expressed genes in pairwise comparison of EST sets2008Inngår i: Bioinformatics and Biology Insights, ISSN 1177-9322, E-ISSN 1177-9322, Vol. 2, s. 215-237Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 42.
    Lindlöf, Angelica
    et al.
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Bräutigam, Marcus
    Department of Cell and Molecular Biology, Medicinaregatan 9C, Box 462, SE405 30 Göteborg, Sweden.
    Chawade, Aakash
    Department of Plant and Environmental Sciences, Gothenburg University, Box 461, SE405 30 Göteborg, Sweden.
    Olsson, Olof
    Department of Plant and Environmental Sciences, Gothenburg University, Box 461, SE405 30 Göteborg, Sweden.
    Olsson, Björn
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    In silico analysis of promoter regions from cold-induced genes in rice (Oryza sativa L.) and Arabidopsis thaliana reveals the importance of combinatorial control2009Inngår i: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 25, nr 11, s. 1345-1348Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Motivation:Cold acclimation involves a number of different cellularprocesses that together increase the freezing tolerance of anorganism. The DREB1/CBFs are transcription factors (TFs) thatare prominent in the regulation of cold responses in Arabidopsisthaliana, rice and many other crops. We investigated if theexpression of DREB1/CBFs and co-expressed genes relies on combinatorialcontrol by several TFs. Our results support this notion andindicate that methods for studying the regulation of complexcellular processes should include identification of combinationsof motifs, in addition to searching for individual overrepresentedbinding sites.

  • 43.
    Lindlöf, Angelica
    et al.
    Högskolan i Skövde, Institutionen för datavetenskap.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för datavetenskap.
    Genetic network inference: the effects of preprocessing2003Inngår i: Biosystems (Amsterdam. Print), ISSN 0303-2647, E-ISSN 1872-8324, Vol. 72, nr 3, s. 229-239Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Clustering of gene expression data and gene network inference from such data has been a major research topic in recent years. In clustering, pairwise measurements are performed when calculating the distance matrix upon which the clustering is based. Pairwise measurements can also be used for gene network inference, by deriving potential interactions above a certain correlation or distance threshold. Our experiments show how interaction networks derived by this simple approach exhibit low—but significant—sensitivity and specificity. We also explore the effects that normalization and prefiltering have on the results of methods for identifying interactions from expression data. Before derivation of interactions or clustering, preprocessing is often performed by applying normalization to rescale the expression profiles and prefiltering where genes that do not appear to contribute to regulation are removed. In this paper, different ways of normalizing in combination with different distance measurements are tested on both unfiltered and prefiltered data, different prefiltering criteria are considered.

  • 44.
    Lubovac, Zelmina
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Corne, David
    Gamalielsson, Jonas
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Weighted Cohesiveness for Identification of Functional Modules and their Interconnectivity2007Inngår i: Bioinformatics Research and Development: First International Conference, BIRD ’07, Springer Berlin/Heidelberg, 2007, s. 185-198Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Systems biology offers a holistic perspective where individual proteins are viewed as elements in a network of protein-protein interactions (PPI), in which the proteins have contextual functions within functional modules. In order to facilitate the identification and analysis of such modules, we have previously proposed a Gene Ontology-weighted clustering coefficient for identification of modules in PPI networks and a method, named SWEMODE (Semantic WEights for MODule Elucidation), where this measure is used to identify network modules. Here, we introduce novel aspects of the method that are tested and evaluated. One of the aspects that we consider is to use the k-core graph instead of the original protein-protein interaction graph.Also, by taking the spatial aspect into account, by using the GO cellular component annotation when calculating weighted cohesiveness, we are able to improve the results compared to previous work where only two of the GO aspects (molecular function and biological process) were combined. We here evaluate the predicted modules by calculating their overlap with MIPS functional complexes. In addition, we identify the “most frequent” proteins, i.e. the proteins that most frequently participate in overlapping modules. We also investigate the role of these proteins in the interconnectivity between modules. We find that the majority of identified proteins are involved in the assembly and arrangement of cell structures, such as the cell wall and cell envelope.

  • 45.
    Lubovac, Zelmina
    et al.
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Gamalielsson, Jonas
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Combining functional and topological properties to identify core modules in protein interaction networks2006Inngår i: Proteins: Structure, Function, and Bioinformatics, ISSN 0887-3585, E-ISSN 1097-0134, Vol. 64, nr 4, s. 948-959Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 46.
    Lubovac, Zelmina
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Gamalielsson, Jonas
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Lindlöf, Angelica
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Exploring protein networks with a semantic similarity measure across Gene Ontology2005Inngår i: Proceedings of the 8th Joint Conference on Information Sciences, Vols 1-3 / [ed] Blair, S., Durham, NC: Joint Conference on Information Sciences , 2005, s. 1203-1208Konferansepaper (Fagfellevurdert)
  • 47.
    Lubovac, Zelmina
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Towards Reverse Engineering of Genetic Regulatory Networks2003Rapport (Annet vitenskapelig)
    Abstract [en]

    The major goal of computational biology is to derive regulatory interactions between genes from large-scale gene expression data and other biological sources. There have been many attempts to reach this goal, but the field needs more research before we can claim that we have reached a complete understanding of reverse engineering of regulatory networks. One of the aspects that have not been considered to a great extent in the development of reverse engineering approaches is combinatorial regulation. Combinatorial regulation can be obtained by the presence of modular architectures in regulation, where multiple binding sites for multiple transcription factors are combined into modular units.

    When modelling regulatory networks, genes are often considered as "black boxes", where gene expression level is an input signal and changed level of expression is the output. We need to shed light on reverse engineering of regulatory networks by modelling the gene "boxes" at a more detailed level of information, e.g., by using regulatory elements as input to gene boxes as a complement to expression levels. Another problem in the context of inferring regulatory networks is the difficulty of validating inferred interactions because it is practically impossible to test and experimentally confirm hundreds to thousands of predicted interactions. Therefore, we need to develop an artificial network to evaluate the developed method for reverse engineering. One of the major research questions that will be proposed in this work is: Can we reverse engineer the cis-regulatory logic controlling the network organised by modular units?

    This work is aiming to give an overview of possible research directions in this field as well as the chosen direction for the future work where more research is needed. It also gives a theoretical foundation for the reverse engineering problem, where key aspects are reviewed.

  • 48.
    Lubovac, Zelmina
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Gamalielsson, Jonas
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Combining topological characteristics and domain knowledge reveals functional modules in protein interaction networks2005Inngår i: Proceedings of CompBioNets 2005: Algorithms and Computational Methods for Biochemical and Evolutionary Networks / [ed] Marie-France Sagot and Katia S. Guimaraes, 2005, s. 93-106Konferansepaper (Fagfellevurdert)
  • 49.
    Lubovac, Zelmina
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Gamalielsson, Jonas
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Weighted Clustering Coefficient for Identifying Modular Formations in Protein-Protein Interaction Networks2006Inngår i: Proceedings of World Academy of Science, Engineering and Technology, Vol 14 / [ed] C. Ardil, World Academy of Science, Engineering and Technology , 2006, s. 122-127Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper describes a novel approach for deriving modules from protein-protein interaction networks, which combines functional information with topological properties of the network. This approach is based on weighted clustering coefficient, which uses weights representing the functional similarities between the proteins. These weights are calculated according to the semantic similarity between the proteins, which is based on their Gene Ontology terms. We recently proposed an algorithm for identification of functional modules, called SWEMODE (Semantic WEights for MODule Elucidation), that identifies dense sub-graphs containing functionally similar proteins. The rational underlying this approach is that each module can be reduced to a set of triangles (protein triplets connected to each other). Here, we propose considering semantic similarity weights of all triangle-forming edges between proteins. We also apply varying semantic similarity thresholds between neighbours of each node that are not neighbours to each other (and hereby do not form a triangle), to derive new potential triangles to include in module-defining procedure. The results show an improvement of pure topological approach, in terms of number of predicted modules that match known complexes.

  • 50.
    Möllerström, Elin
    et al.
    University of Gothenburg.
    Delle, Ulla
    University of Gothenburg.
    Danielsson, Anna
    University of Gothenburg.
    Parris, Toshima
    University of Gothenburg.
    Olsson, Björn
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Karlsson, Per
    University of Gothenburg.
    Helou, Khalil
    University of Gothenburg.
    High-resolution genomic profiling to predict 10-year overall survival in node-negative breast cancer2010Inngår i: Cancer Genetics and Cytogenetics, ISSN 2210-7762, E-ISSN 2210-7770, Vol. 198, nr 2, s. 79-89Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Women with clinically node-negative breast cancer have a better prognosis than do those with axillary lymph node metastasis. Nonetheless, ~20% of node-negative patients die within 15 years of diagnosis, and thus additional prognostic markers are greatly needed. To identify specific copy number alterations (CNAs) that differed in frequency between 10-year survivors and deceased patients with node-negative breast cancer, array comparative genomic hybridization (aCGH) was applied to 41 primary node-negative breast tumors. Fisher's exact test was used to identify significantly different CNAs between 10-year survivors and deceased patients. Losses at 8p21.2~p21.3, 8p23.1~p23.2, Xp21.3, and Xp22.31~p22.33 were significantly more common in tumors from deceased patients, suggesting that these alterations may contribute to tumor aggressiveness. Gains at 1q25.2~q25.3 and 1q31.3~q41 were more prevalent in tumors from survivors; specific gains at these genomic regions may inhibit further tumor progression, resulting in a less aggressive form of node-negative breast cancer. Evaluation of the identified CNAs in an independent external data set verified the prognistic potential of the 1q31.3~q41 region. Although further extensive validation is needed, the prognostic CNAs identified in this work may in time facilitate the clinical assessment of breast cancer.

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