ArticleNucleic acids research2021
OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions.
Article in Nucleic acids research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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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.
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Who cites it
17 citing papers in PubMed.
- CASHeart: A database of single cells chromatin accessibility for the human heart.Quantitative biology (Beijing, China) · 2025Article
- CREATE: cell-type-specific cis-regulatory element identification via discrete embedding.Nature communications · 2025Article
- EpiGePT: a pretrained transformer-based language model for context-specific human epigenomics.Genome biology · 2024Article
- Hierarchical learning of gastric cancer molecular subtypes by integrating multi-modal DNA-level omics data and clinical stratification.Quantitative biology (Beijing, China) · 2024Article
- Classifying breast cancer subtypes on multi-omics data via sparse canonical correlation analysis and deep learning.BMC bioinformatics · 2024Article
- scCASE: accurate and interpretable enhancement for single-cell chromatin accessibility sequencing data.Nature communications · 2024Article
- OpenAnnotateApi: Python and R packages to efficiently annotate and analyze chromatin accessibility of genomic regions.Bioinformatics advances · 2024Article
- Cofea: correlation-based feature selection for single-cell chromatin accessibility data.Briefings in bioinformatics · 2023Article
- scIBD: a self-supervised iterative-optimizing model for boosting the detection of heterotypic doublets in single-cell chromatin accessibility data.Genome biology · 2023Article
- DeepDrug: A general graph-based deep learning framework for drug-drug interactions and drug-target interactions prediction.Quantitative biology (Beijing, China) · 2023Article
- PlantCADB: A Comprehensive Plant Chromatin Accessibility Database.Genomics, proteomics & bioinformatics · 2023Article
- Translator: AJournal of computational biology : a journal of computational molecular cell biology · 2022Article
- DeepCAGE: Incorporating Transcription Factors in Genome-wide Prediction of Chromatin Accessibility.Genomics, proteomics & bioinformatics · 2022Article
- MOMA: a multi-task attention learning algorithm for multi-omics data interpretation and classification.Bioinformatics (Oxford, England) · 2022Article
- Openness weighted association studies: leveraging personal genome information to prioritize non-coding variants.Bioinformatics (Oxford, England) · 2021Article
- DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers.Genomics, proteomics & bioinformatics · 2021Article
- stPlus: a reference-based method for the accurate enhancement of spatial transcriptomics.Bioinformatics (Oxford, England) · 2021Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chromatin accessibility, as a powerful marker of active DNA regulatory elements, provides valuable information for understanding regulatory mechanisms. The revolution in high-throughput methods has accumulated massive chromatin accessibility profiles in public repositories. Nevertheless, utilization of these data is hampered by cumbersome collection, time-consuming processing, and manual chromatin accessibility (openness) annotation of genomic regions. To fill this gap, we developed OpenAnnotate (http://health.tsinghua.edu.cn/openannotate/) as the first web server for efficiently annotating openness of massive genomic regions across various biosample types, tissues, and biological systems. In addition to the annotation resource from 2729 comprehensive profiles of 614 biosample types of human and mouse, OpenAnnotate provides user-friendly functionalities, ultra-efficient calculation, real-time browsing, intuitive visualization, and elaborate application notebooks. We show its unique advantages compared to existing databases and toolkits by effectively revealing cell type-specificity, identifying regulatory elements and 3D chromatin contacts, deciphering gene functional relationships, inferring functions of transcription factors, and unprecedentedly promoting single-cell data analyses. We anticipate OpenAnnotate will provide a promising avenue for researchers to construct a more holistic perspective to understand regulatory mechanisms.
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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 OpenQuestion graph.