his.sePublications
Change search
Refine search result
1 - 2 of 2
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Lindlöf, Angelica
    et al.
    University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Life Sciences.
    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
    University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Life Sciences.
    In silico analysis of promoter regions from cold-induced genes in rice (Oryza sativa L.) and Arabidopsis thaliana reveals the importance of combinatorial control2009In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 25, no 11, p. 1345-1348Article in journal (Refereed)
    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.

  • 2.
    Weishaupt, Holger
    et al.
    Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden.
    Johansson, Patrik
    Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden.
    Sundström, Anders
    Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden.
    Lubovac-Pilav, Zelmina
    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.
    Nelander, Sven
    Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden.
    Swartling, Fredrik J.
    Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden.
    Batch-normalization of cerebellar and medulloblastoma gene expression datasets utilizing empirically defined negative control genes2019In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 35, no 18, p. 3357-3364Article in journal (Refereed)
    Abstract [en]

    Motivation: Medulloblastoma (MB) is a brain cancer predominantly arising in children. Roughly 70% of patients are cured today, but survivors often suffer from severe sequelae. MB has been extensively studied by molecular profiling, but often in small and scattered cohorts. To improve cure rates and reduce treatment side effects, accurate integration of such data to increase analytical power will be important, if not essential.

    Results: We have integrated 23 transcription datasets, spanning 1350 MB and 291 normal brain samples. To remove batch effects, we combined the Removal of Unwanted Variation (RUV) method with a novel pipeline for determining empirical negative control genes and a panel of metrics to evaluate normalization performance. The documented approach enabled the removal of a majority of batch effects, producing a large-scale, integrative dataset of MB and cerebellar expression data. The proposed strategy will be broadly applicable for accurate integration of data and incorporation of normal reference samples for studies of various diseases. We hope that the integrated dataset will improve current research in the field of MB by allowing more large-scale gene expression analyses.

1 - 2 of 2
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf