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| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Baty, Florent Rüdiger, Jochen Miglino, Nicola Kern, Lukas Borger, Peter Brutsche, Martin |
| Abstract | Background Interpretation of gene expression microarray data in the light of external information on both columns and rows (experimental variables and gene annotations) facilitates the extraction of pertinent information hidden in these complex data. Biologists classically interpret genes of interest after retrieving functional information from a subset of genes of interest. Transcription factors play an important role in orchestrating the regulation of gene expression. Their activity can be deduced by examining the presence of putative transcription factors binding sites in the gene promoter regions. Results In this paper we present the multivariate statistical method RLQ which aims to analyze microarray data where additional information is available on both genes and samples. As an illustrative example, we applied RLQ methodology to analyze transcription factor activity associated with the time-course effect of steroids on the growth of primary human lung fibroblasts. RLQ could successfully predict transcription factor activity, and could integrate various other sources of external information in the main frame of the analysis. The approach was validated by means of alternative statistical methods and biological validation. Conclusions RLQ provides an efficient way of extracting and visualizing structures present in a gene expression dataset by directly modeling the link between experimental variables and gene annotations. |
| Related Links | https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/1471-2105-14-178.pdf |
| Ending Page | 15 |
| Page Count | 15 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| ISSN | 14712105 |
| DOI | 10.1186/1471-2105-14-178 |
| Journal | BMC Bioinformatics |
| Issue Number | 1 |
| Volume Number | 14 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2013-06-06 |
| Access Restriction | Open |
| Subject Keyword | Bioinformatics Microarrays Computational Biology Computer Appl. in Life Sciences Algorithms Gene Ontology Correspondence Analysis Transcription Factor Activity Transcription Factor Binding Site Ordination Method Computational Biology/Bioinformatics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Molecular Biology Biochemistry Computer Science Applications Applied Mathematics Structural Biology |
| Journal Impact Factor | 2.9/2023 |
| 5-Year Journal Impact Factor | 3.6/2023 |
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