Probabilistic partitioning methods to find significant patterns in ChIP-Seq data
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Title
Probabilistic partitioning methods to find significant patterns in ChIP-Seq data
Authors
Keywords
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Journal
BIOINFORMATICS
Volume 30, Issue 17, Pages 2406-2413
Publisher
Oxford University Press (OUP)
Online
2014-05-09
DOI
10.1093/bioinformatics/btu318
References
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Related references
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- NCBI GEO: archive for functional genomics data sets—update
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- CATCHprofiles: Clustering and Alignment Tool for ChIP Profiles
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- ArchAlign: Coordinate-free chromatin alignment reveals novel architectures
- (2011) William Lai et al. GENOME BIOLOGY
- seqMINER: an integrated ChIP-seq data interpretation platform
- (2010) Tao Ye et al. NUCLEIC ACIDS RESEARCH
- Histone H3K27ac separates active from poised enhancers and predicts developmental state
- (2010) M. P. Creyghton et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Predictive chromatin signatures in the mammalian genome
- (2009) G. C. Hon et al. HUMAN MOLECULAR GENETICS
- JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles
- (2009) Elodie Portales-Casamar et al. NUCLEIC ACIDS RESEARCH
- Dynamic Regulation of Nucleosome Positioning in the Human Genome
- (2008) Dustin E. Schones et al. CELL
- ChromaSig: A Probabilistic Approach to Finding Common Chromatin Signatures in the Human Genome
- (2008) Gary Hon et al. PLoS Computational Biology
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