ArticleNucleic acids research2018
Dynamic motif occupancy (DynaMO) analysis identifies transcription factors and their binding sites driving dynamic biological processes.
Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
9 citing papers in PubMed.
- HDAC3 integrates TGF-β and microbial cues to program tuft cell biogenesis and diurnal rhythms in mucosal immune surveillance.Science immunology · 2024Article
- A comprehensive review of computational prediction of genome-wide features.Briefings in bioinformatics · 2020Article
- The intestinal microbiota programs diurnal rhythms in host metabolism through histone deacetylase 3.Science (New York, N.Y.) · 2019Article
- Demethylation of the Protein Phosphatase PP2A Promotes Demethylation of Histones to Enable Their Function as a Methyl Group Sink.Molecular cell · 2019Article
- Stochasticity in transcriptional expression of a negative regulator of Arabidopsis ABA network.3 Biotech · 2019Article
- Engineering renal epithelial cells: programming and directed differentiation towards glomerular podocyte's progenitor and mature podocyte.American journal of translational research · 2019Review
- Stress response factors drive regrowth of quiescent cells.Current genetics · 2018Review
- Elucidating the Role of Chromatin State and Transcription Factors on the Regulation of the Yeast Metabolic Cycle: A Multi-Omic Integrative Approach.Frontiers in genetics · 2018Article
- Msn2/4 regulate expression of glycolytic enzymes and control transition from quiescence to growth.eLife · 2017Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Biological processes are usually associated with genome-wide remodeling of transcription driven by transcription factors (TFs). Identifying key TFs and their spatiotemporal binding patterns are indispensable to understanding how dynamic processes are programmed. However, most methods are designed to predict TF binding sites only. We present a computational method, dynamic motif occupancy analysis (DynaMO), to infer important TFs and their spatiotemporal binding activities in dynamic biological processes using chromatin profiling data from multiple biological conditions such as time-course histone modification ChIP-seq data. In the first step, DynaMO predicts TF binding sites with a random forests approach. Next and uniquely, DynaMO infers dynamic TF binding activities at predicted binding sites using their local chromatin profiles from multiple biological conditions. Another landmark of DynaMO is to identify key TFs in a dynamic process using a clustering and enrichment analysis of dynamic TF binding patterns. Application of DynaMO to the yeast ultradian cycle, mouse circadian clock and human neural differentiation exhibits its accuracy and versatility. We anticipate DynaMO will be generally useful for elucidating transcriptional programs in dynamic processes.
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Registered trials
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 Socratic graph.