ArticleBioinformatics (Oxford, England)2015
hiHMM: Bayesian non-parametric joint inference of chromatin state maps.
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Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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28citing papers in PubMed
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28 citing papers in PubMed, 59 citations in OpenAlex.
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- Evolution of a distinct chromatin regulatory landscape in brown algae.Nature ecology & evolution · 2026Article
- PlantFUNCO: Integrative Functional Genomics Database Reveals Clues into Duplicates Divergence Evolution.Molecular biology and evolution · 2024Article
- Toward a comprehensive catalog of regulatory elements.Human genetics · 2023Review
- Computational methods to explore chromatin state dynamics.Briefings in bioinformatics · 2022Review
- Learning representations of chromatin contacts using a recurrent neural network identifies genomic drivers of conformation.Nature communications · 2022Article
- Continuous chromatin state feature annotation of the human epigenome.Bioinformatics (Oxford, England) · 2022Article
- Article
- 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
- Tree-Based Co-Clustering Identifies Chromatin Accessibility Patterns Associated With Hematopoietic Lineage Structure.Frontiers in genetics · 2021Article
- Biophysical Review's 'meet the editors series'-a profile of Joshua W. K. Ho.Biophysical reviews · 2020Article
- HMMRATAC: a Hidden Markov ModeleR for ATAC-seq.Nucleic acids research · 2019Article
- A unified encyclopedia of human functional DNA elements through fully automated annotation of 164 human cell types.Genome biology · 2019Article
- TriPCE: A Novel Tri-Clustering Algorithm for Identifying Pan-Cancer Epigenetic Patterns.Frontiers in genetics · 2019Article
- Reveal cell type-specific regulatory elements and their characterized histone code classes via a hidden Markov model.BMC genomics · 2018Article
- Applications of ENCODE data to Systematic Analyses via Data Integration.Current opinion in systems biology · 2018Article
- chromswitch: a flexible method to detect chromatin state switches.Bioinformatics (Oxford, England) · 2018Article
- Integrating ChIP-seq with other functional genomics data.Briefings in functional genomics · 2018Review
- Chromatin-state discovery and genome annotation with ChromHMM.Nature protocols · 2017Review
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Authors and funding
6 authors at 4 institutions in 3 countries.
Kyung-Ah SohnDepartment of Information and Computer Engineering, Ajou University, Suwon 443-749, South Korea, Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea, Systems Biomedical Informatics Research Center, Seoul National University, Seoul 110799, Korea, Victor Chang Cardiac Research Institute, Sydney, NSW 2010, Australia, The University of New South Wales, Sydney, NSW 2052, Australia, Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA and Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA Department of Information and Computer Engineering, Ajou University, Suwon 443-749, South Korea, Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea, Systems Biomedical Informatics Research Center, Seoul National University, Seoul 110799, Korea, Victor Chang Cardiac Research Institute, Sydney, NSW 2010, Australia, The University of New South Wales, Sydney, NSW 2052, Australia, Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA and Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA Department of Information and Computer Engineering, Ajou University, Suwon 443-749, South Korea, Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea, Systems Biomedical Informatics Research Center, Seoul National University, Seoul 110799, Korea, Victor Chang Cardiac Research Institute, Sydney, NSW 2010, Australia, The University of New South Wales, Sydney, NSW 2052, Australia, Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA and Division of Genetics, Department o
Joshua W K HoDepartment of Information and Computer Engineering, Ajou University, Suwon 443-749, South Korea, Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea, Systems Biomedical Informatics Research Center, Seoul National University, Seoul 110799, Korea, Victor Chang Cardiac Research Institute, Sydney, NSW 2010, Australia, The University of New South Wales, Sydney, NSW 2052, Australia, Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA and Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA Department of Information and Computer Engineering, Ajou University, Suwon 443-749, South Korea, Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea, Systems Biomedical Informatics Research Center, Seoul National University, Seoul 110799, Korea, Victor Chang Cardiac Research Institute, Sydney, NSW 2010, Australia, The University of New South Wales, Sydney, NSW 2052, Australia, Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA and Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA Department of Information and Computer Engineering, Ajou University, Suwon 443-749, South Korea, Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea, Systems Biomedical Informatics Research Center, Seoul National University, Seoul 110799, Korea, Victor Chang Cardiac Research Institute, Sydney, NSW 2010, Australia, The University of New South Wales, Sydney, NSW 2052, Australia, Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA and Division of Genetics, Department o
Djordje DjordjevicDepartment of Information and Computer Engineering, Ajou University, Suwon 443-749, South Korea, Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea, Systems Biomedical Informatics Research Center, Seoul National University, Seoul 110799, Korea, Victor Chang Cardiac Research Institute, Sydney, NSW 2010, Australia, The University of New South Wales, Sydney, NSW 2052, Australia, Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA and Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA Department of Information and Computer Engineering, Ajou University, Suwon 443-749, South Korea, Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea, Systems Biomedical Informatics Research Center, Seoul National University, Seoul 110799, Korea, Victor Chang Cardiac Research Institute, Sydney, NSW 2010, Australia, The University of New South Wales, Sydney, NSW 2052, Australia, Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA and Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Hyun-Hwan JeongDepartment of Information and Computer Engineering, Ajou University, Suwon 443-749, South Korea, Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea, Systems Biomedical Informatics Research Center, Seoul National University, Seoul 110799, Korea, Victor Chang Cardiac Research Institute, Sydney, NSW 2010, Australia, The University of New South Wales, Sydney, NSW 2052, Australia, Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA and Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Peter J ParkDepartment of Information and Computer Engineering, Ajou University, Suwon 443-749, South Korea, Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea, Systems Biomedical Informatics Research Center, Seoul National University, Seoul 110799, Korea, Victor Chang Cardiac Research Institute, Sydney, NSW 2010, Australia, The University of New South Wales, Sydney, NSW 2052, Australia, Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA and Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA Department of Information and Computer Engineering, Ajou University, Suwon 443-749, South Korea, Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea, Systems Biomedical Informatics Research Center, Seoul National University, Seoul 110799, Korea, Victor Chang Cardiac Research Institute, Sydney, NSW 2010, Australia, The University of New South Wales, Sydney, NSW 2052, Australia, Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA and Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Ju Han KimDepartment of Information and Computer Engineering, Ajou University, Suwon 443-749, South Korea, Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea, Systems Biomedical Informatics Research Center, Seoul National University, Seoul 110799, Korea, Victor Chang Cardiac Research Institute, Sydney, NSW 2010, Australia, The University of New South Wales, Sydney, NSW 2052, Australia, Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA and Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA Department of Information and Computer Engineering, Ajou University, Suwon 443-749, South Korea, Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea, Systems Biomedical Informatics Research Center, Seoul National University, Seoul 110799, Korea, Victor Chang Cardiac Research Institute, Sydney, NSW 2010, Australia, The University of New South Wales, Sydney, NSW 2052, Australia, Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA and Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
UNSW Sydney · AUNational University College · PRSeoul National University · KRVictor Chang Cardiac Research Institute · AU
Funding
Genome-Wide Mapping of Chromosomal Proteins in DrosophiliaU01HG004258 · NHGRI · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · PI KARPEN, GARY H · 2007 to 2011
$9.6MNHGRI NIH HHS U01HG004258
Abstract
motivationGenome-wide mapping of chromatin states is essential for defining regulatory elements and inferring their activities in eukaryotic genomes. A number of hidden Markov model (HMM)-based methods have been developed to infer chromatin state maps from genome-wide histone modification data for an individual genome. To perform a principled comparison of evolutionarily distant epigenomes, we must consider species-specific biases such as differences in genome size, strength of signal enrichment and co-occurrence patterns of histone modifications.
resultsHere, we present a new Bayesian non-parametric method called hierarchically linked infinite HMM (hiHMM) to jointly infer chromatin state maps in multiple genomes (different species, cell types and developmental stages) using genome-wide histone modification data. This flexible framework provides a new way to learn a consistent definition of chromatin states across multiple genomes, thus facilitating a direct comparison among them. We demonstrate the utility of this method using synthetic data as well as multiple modENCODE ChIP-seq datasets.
conclusionThe hierarchical and Bayesian non-parametric formulation in our approach is an important extension to the current set of methodologies for comparative chromatin landscape analysis. AVAILABILITY AND IMPLEMENTATION: Source codes are available at https://github.com/kasohn/hiHMM. Chromatin data are available at http://encode-x.med.harvard.edu/data_sets/chromatin/.
Indexed as
Bayes TheoremSoftwareStatistics, NonparametricAnimalsChromatinChromatin ImmunoprecipitationComputational BiologyDrosophila melanogasterGene Expression Regulation, DevelopmentalHistonesHumansPromoter Regions, GeneticRegulatory Sequences, Nucleic AcidChromatinHistones
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