ArticleNature methods2015
Predicting the human epigenome from DNA motifs.
Article in Nature methods, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
82 citing papers in PubMed, 138 citations in OpenAlex.
- An atlas of transcription factor cooperation reveals how motif readers shape regulatory output.bioRxiv : the preprint server for biology · 2026Article
- Population-level Variability in Genome-wide Repressive Histone Marks in a Fungal Wheat Pathogen.Genome biology and evolution · 2026Article
- Machine and Deep Learning Reveal Sequence Determinants Encoding Bivalent Histone Modifications.Communications biology · 2026Article
- Deciphering Sequence Determinants of Zygotic Genome Activation Genes: Insights From Machine Learning and the ZGAExplorer Platform.Cell proliferation · 2025Article
- Epigenetic motifs distinguishing endogenous from exogenous retroviral integrants.Journal of virology · 2025Article
- TFscope: systematic analysis of the sequence features involved in the binding preferences of transcription factors.Genome biology · 2024Article
- Quiescence enables unrestricted cell fate in naive embryonic stem cells.Nature communications · 2024Article
- Bottom-up data integration in polymer models of chromatin organization.Biophysical journal · 2024Article
- Advancing Regulatory Genomics With Machine Learning.Bioinformatics and biology insights · 2024Review
- Widespread effects of DNA methylation and intra-motif dependencies revealed by novel transcription factor binding models.Nucleic acids research · 2023Article
- Predicting regional somatic mutation rates using DNA motifs.PLoS computational biology · 2023Article
- Underlying causes for prevalent false positives and false negatives in STARR-seq data.NAR genomics and bioinformatics · 2023Article
- iCpG-Pos: an accurate computational approach for identification of CpG sites using positional features on single-cell whole genome sequence data.Bioinformatics (Oxford, England) · 2023Article
- Prioritizing genes associated with brain disorders by leveraging enhancer-promoter interactions in diverse neural cells and tissues.Genome medicine · 2023Article
- Integrative modeling of lncRNA-chromatin interaction maps reveals diverse mechanisms of nuclear retention.BMC genomics · 2023Article
- Recall DNA methylation levels at low coverage sites using a CNN model in WGBS.PLoS computational biology · 2023Article
- YTH Domain Proteins Play an Essential Role in Rice Growth and Stress Response.Plants (Basel, Switzerland) · 2022Article
- NF-κB signaling controls H3K9me3 levels at intronic LINE-1 and hematopoietic stem cell genes in cis.The Journal of experimental medicine · 2022Article
- Annotating functional effects of non-coding variants in neuropsychiatric cell types by deep transfer learning.PLoS computational biology · 2022Article
- Machine learning: its challenges and opportunities in plant system biology.Applied microbiology and biotechnology · 2022Review
22 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
The epigenome is established and maintained by the site-specific recruitment of chromatin-modifying enzymes and their cofactors. Identifying the cis elements that regulate epigenomic modification is critical for understanding the regulatory mechanisms that control gene expression patterns. We present Epigram, an analysis pipeline that predicts histone modification and DNA methylation patterns from DNA motifs. The identified cis elements represent interactions with the site-specific DNA-binding factors that establish and maintain epigenomic modifications. We cataloged the cis elements in embryonic stem cells and four derived lineages and found numerous motifs that have location preference, such as at the center of H3K27ac or at the edges of H3K4me3 and H3K9me3, which provides mechanistic insight about the shaping of the epigenome. The Epigram pipeline and predictive motifs are at http://wanglab.ucsd.edu/star/epigram/.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.