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Augustin, R. ; Lichtenthaler, S.F.* ; Greeff, M. ; Hansen, J. ; Wurst, W. ; Trümbach, D.

Bioinformatics identification of modules of transcription factor binding sites in Alzheimer's disease-related genes by in silico promoter analysis and microarrays.

Int. J. Alzheimers Dis. 2011:154325 (2011)
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The molecular mechanisms and genetic risk factors underlying Alzheimer's disease (AD) pathogenesis are only partly understood. To identify new factors, which may contribute to AD, different approaches are taken including proteomics, genetics, and functional genomics. Here, we used a bioinformatics approach and found that distinct AD-related genes share modules of transcription factor binding sites, suggesting a transcriptional coregulation. To detect additional coregulated genes, which may potentially contribute to AD, we established a new bioinformatics workflow with known multivariate methods like support vector machines, biclustering, and predicted transcription factor binding site modules by using in silico analysis and over 400 expression arrays from human and mouse. Two significant modules are composed of three transcription factor families: CTCF, SP1F, and EGRF/ZBPF, which are conserved between human and mouse APP promoter sequences. The specific combination of in silico promoter and multivariate analysis can identify regulation mechanisms of genes involved in multifactorial diseases.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter no keywords
e-ISSN 2090-0252
Quellenangaben Band: 2011, Heft: , Seiten: , Artikelnummer: 154325 Supplement: ,
Verlag Hindawi
Begutachtungsstatus Peer reviewed