ArticleBioinformatics (Oxford, England)2009
PASTAA: identifying transcription factors associated with sets of co-regulated genes.
Article in Bioinformatics (Oxford, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 101 papers, 3 of them syntheses that pooled it.
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101 citing papers in PubMed, 3 syntheses or guidelines pooled it, 160 citations in OpenAlex.
- Pooled it
- Improved linking of motifs to their TFs using domain information.Bioinformatics (Oxford, England) · 2020Pooled it
- Pooled it
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- Deep characterization of human γδ T cell subsets defines shared and lineage-specific traits.Frontiers in immunology · 2023Article
- Patterns of transcription factor binding and epigenome at promoters allow interpretable predictability of multiple functions of non-coding and coding genes.Computational and structural biotechnology journal · 2023Article
- Targeting HIC1/TGF-β axis-shaped prostate cancer microenvironment restrains its progression.Cell death & disease · 2022Article
- β-Klotho promotes glycolysis and glucose-stimulated insulin secretion via GP130.Nature metabolism · 2022Article
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- Exome Sequencing Reveals Genetic Variability and Identifies Chronic Prognostic Loci in Chinese Sarcoidosis Patients.Frontiers in oncology · 2022Article
41 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationA major challenge in regulatory genomics is the identification of associations between functional categories of genes (e.g. tissues, metabolic pathways) and their regulating transcription factors (TFs). While, for a limited number of categories, the regulating TFs are already known, still for many functional categories the responsible factors remain to be elucidated.
resultsWe put forward a novel method (PASTAA) for detecting transcriptions factors associated with functional categories, which utilizes the prediction of binding affinities of a TF to promoters. This binding strength information is compared to the likelihood of membership of the corresponding genes in the functional category under study. Coherence between the two ranked datasets is seen as an indicator of association between a TF and the category. PASTAA is applied primarily to the determination of TFs driving tissue-specific expression. We show that PASTAA is capable of recovering many TFs acting tissue specifically and, in addition, provides novel associations so far not detected by alternative methods. The application of PASTAA to detect TFs involved in the regulation of tissue-specific gene expression revealed a remarkable number of experimentally supported associations. The validated success for various datasets implies that PASTAA can directly be applied for the detection of TFs associated with newly derived gene sets. AVAILABILITY: The PASTAA source code as well as a corresponding web interface is freely available at http://trap.molgen.mpg.de.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.