Literature DB >> 23266811

LinkNMF: identification of histone modification modules in the human genome using nonnegative matrix factorization.

Inkyung Jung1, Dongsup Kim.   

Abstract

Histone modifications are ubiquitous processes involved in various cellular mechanisms. Systemic analysis of multiple chromatin modifications has been used to characterize various chromatin states associated with functional DNA elements, gene expression, and specific biological functions. However, identification of modular modification patterns is still required to understand the functional associations between histone modification patterns and specific chromatin/DNA binding factors. To recognize modular modification patterns, we developed a novel algorithm that combines nonnegative matrix factorization (NMF) and a clique-detection algorithm. We applied it, called LinkNMF, to generate a comprehensive modification map in human CD4+ T cell promoter regions. Initially, we identified 11 modules not recognized by conventional approaches. The modules were grouped into two major classes: gene activation and repression. We found that genes targeted by each module were enriched with distinguishable biological functions, suggesting that each modular pattern plays a unique functional role. To explain the formation of modular patterns, we investigated the module-specific binding patterns of chromatin regulators. Application of LinkNMF to histone modification maps of diverse cells and developmental stages will be helpful for understanding how histone modifications regulate gene expression. The algorithm is available on our website at biodb.kaist.ac.kr/LinkNMF.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 23266811     DOI: 10.1016/j.gene.2012.11.027

Source DB:  PubMed          Journal:  Gene        ISSN: 0378-1119            Impact factor:   3.688


  3 in total

1.  CloudNMF: a MapReduce implementation of nonnegative matrix factorization for large-scale biological datasets.

Authors:  Ruiqi Liao; Yifan Zhang; Jihong Guan; Shuigeng Zhou
Journal:  Genomics Proteomics Bioinformatics       Date:  2013-08-08       Impact factor: 7.691

2.  MultiFacTV: module detection from higher-order time series biological data.

Authors:  Xutao Li; Yunming Ye; Michael Ng; Qingyao Wu
Journal:  BMC Genomics       Date:  2013-10-01       Impact factor: 3.969

3.  Comparisons of non-Gaussian statistical models in DNA methylation analysis.

Authors:  Zhanyu Ma; Andrew E Teschendorff; Hong Yu; Jalil Taghia; Jun Guo
Journal:  Int J Mol Sci       Date:  2014-06-16       Impact factor: 5.923

  3 in total

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