{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,1,28]],"date-time":"2023-01-28T05:22:24Z","timestamp":1674883344644},"reference-count":5,"publisher":"Oxford University Press (OUP)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,6,15]]},"abstract":"Abstract<\/jats:title>\n Summary: Hidden Markov models (HMMs) are flexible and widely used in scientific studies. Particularly in genomics and genetics, there are multiple distinct regimes in the genome within each of which the relationships among multivariate features are distinct. Examples include differential gene regulation depending on gene functions and experimental conditions, and varying combinatorial patterns of multiple transcription factors. We developed a software package called MRHMMs (Multivariate Regression Hidden Markov Models and the variantS) that accommodates a variety of HMMs that can be flexibly applied to many biological studies and beyond. MRHMMs supplements existing HMM software packages in two aspects. First, MRHMMs provides a diverse set of emission probability structures, including mixture of multivariate normal distributions and (logistic) regression models. Second, MRHMMs is computationally efficient for analyzing large data-sets generated in current genome-wide studies. Especially, the software is written in C for the speed advantage and further amenable to implement alternative models to meet users\u2019 own purposes.<\/jats:p>\n Availability and implementation: http:\/\/sourceforge.net\/projects\/mrhmms\/<\/jats:p>\n Contact: \u00a0ghoshd@psu.edu or yuzhang@stat.psu.edu<\/jats:p>\n Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btu070","type":"journal-article","created":{"date-parts":[[2014,2,21]],"date-time":"2014-02-21T01:58:58Z","timestamp":1392947938000},"page":"1755-1756","source":"Crossref","is-referenced-by-count":1,"title":["MRHMMs: Multivariate Regression Hidden Markov Models and the variantS"],"prefix":"10.1093","volume":"30","author":[{"given":"Yeonok","family":"Lee","sequence":"first","affiliation":[{"name":"1 Department of Statistics and 2Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16803, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Debashis","family":"Ghosh","sequence":"additional","affiliation":[{"name":"1 Department of Statistics and 2Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16803, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ross C.","family":"Hardison","sequence":"additional","affiliation":[{"name":"1 Department of Statistics and 2Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16803, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Zhang","sequence":"additional","affiliation":[{"name":"1 Department of Statistics and 2Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16803, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2014,2,19]]},"reference":[{"key":"2023012711062224900_btu070-B1","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1214\/aoms\/1177697196","article-title":"A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains","volume":"41","author":"Baum","year":"1970","journal-title":"Ann. Math. Stat."},{"key":"2023012711062224900_btu070-B2","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.jtbi.2012.06.009","article-title":"Histone modification profiles characterize function-specific gene regulation","volume":"310","author":"Jung","year":"2012","journal-title":"J. Theor. Biol."},{"key":"2023012711062224900_btu070-B3","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1038\/nbt.1630","article-title":"Great improves functional interpretation of cis-regulatory regions","volume":"28","author":"McLean","year":"2010","journal-title":"Nat. Biotechnol."},{"key":"2023012711062224900_btu070-B4","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1109\/TIT.1967.1054010","article-title":"Error bounds for convolutional codes and an asymptotically optimum decoding algorithm","volume":"13","author":"Viterbi","year":"1967","journal-title":"IEEE Trans. Inf. Theory"},{"key":"2023012711062224900_btu070-B5","doi-asserted-by":"crossref","first-page":"1659","DOI":"10.1101\/gr.125088.111","article-title":"Dynamics of the epigenetic landscape during erythroid differentiation after gata1 restoration","volume":"21","author":"Wu","year":"2011","journal-title":"Genome Res."}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/30\/12\/1755\/48926214\/bioinformatics_30_12_1755.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/30\/12\/1755\/48926214\/bioinformatics_30_12_1755.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,27]],"date-time":"2023-01-27T11:06:34Z","timestamp":1674817594000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/30\/12\/1755\/380854"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,2,19]]},"references-count":5,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2014,6,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btu070","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2014,6,15]]},"published":{"date-parts":[[2014,2,19]]}}}