ArticleNucleic acids research2016
Jointly characterizing epigenetic dynamics across multiple human cell types.
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 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
52 citing papers in PubMed.
- Pan-cell type continuous chromatin state annotation of 1,698 epigenomes from the International Human Epigenome Consortium.Genome biology · 2026Article
- chromIDEAS reveals epigenetic dynamics via multi-dimensional clustering of chromatin states.Nucleic acids research · 2026Article
- Chromatin state dynamics during the Plasmodium falciparum intraerythrocytic development cycle.BMC genomics · 2026Article
- Epilogos: information-theoretic navigation of multi-tissue functional genomic annotations.bioRxiv : the preprint server for biology · 2025Article
- Article
- Interspecies regulatory landscapes and elements revealed by novel joint systematic integration of human and mouse blood cell epigenomes.Genome research · 2024Article
- Genome-wide large-scale multi-trait analysis characterizes global patterns of pleiotropy and unique trait-specific variants.Nature communications · 2024Article
- Robust chromatin state annotation.Genome research · 2024Article
- JMnorm: a novel joint multi-feature normalization method for integrative and comparative epigenomics.Nucleic acids research · 2024Article
- A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology.Nature communications · 2023Article
- Toward a comprehensive catalog of regulatory elements.Human genetics · 2023Review
- Snapshot: a package for clustering and visualizing epigenetic history during cell differentiation.BMC bioinformatics · 2023Article
- Continuous chromatin state feature annotation of the human epigenome.Bioinformatics (Oxford, England) · 2022Article
- Machine learning: its challenges and opportunities in plant system biology.Applied microbiology and biotechnology · 2022Review
- Universal annotation of the human genome through integration of over a thousand epigenomic datasets.Genome biology · 2022Article
- Segmentation and genome annotation algorithms for identifying chromatin state and other genomic patterns.PLoS computational biology · 2021Review
- NucHMM: a method for quantitative modeling of nucleosome organization identifying functional nucleosome states distinctly associated with splicing potentiality.Genome biology · 2021Article
- Annotation of chromatin states in 66 complete mouse epigenomes during development.Communications biology · 2021Article
- AI applications in functional genomics.Computational and structural biotechnology journal · 2021Review
- Tree-Based Co-Clustering Identifies Chromatin Accessibility Patterns Associated With Hematopoietic Lineage Structure.Frontiers in genetics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Advanced sequencing technologies have generated a plethora of data for many chromatin marks in multiple tissues and cell types, yet there is lack of a generalized tool for optimal utility of those data. A major challenge is to quantitatively model the epigenetic dynamics across both the genome and many cell types for understanding their impacts on differential gene regulation and disease. We introduce IDEAS, an integrative and discriminative epigenome annotation system, for jointly characterizing epigenetic landscapes in many cell types and detecting differential regulatory regions. A key distinction between our method and existing state-of-the-art algorithms is that IDEAS integrates epigenomes of many cell types simultaneously in a way that preserves the position-dependent and cell type-specific information at fine scales, thereby greatly improving segmentation accuracy and producing comparable annotations across cell types.
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.