A penalized Bayesian approach to predicting sparse protein-DNA binding landscapes

Bioinformatics

Volumn 30, Issue 5, 2014, Pages 636-643

  Levinson, Matthew ^a   Zhou, Qing ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DNA BINDING PROTEIN; TRANSCRIPTION FACTOR;

ALGORITHM; ANIMAL; ARTICLE; BAYES THEOREM; BINDING SITE; CHROMATIN IMMUNOPRECIPITATION; COMPUTER PROGRAM; DNA SEQUENCE; EMBRYONIC STEM CELL; GENOMICS; METABOLISM; METHODOLOGY; MOUSE; PROMOTER REGION;

ALGORITHMS; ANIMALS; BAYES THEOREM; BINDING SITES; CHROMATIN IMMUNOPRECIPITATION; DNA-BINDING PROTEINS; EMBRYONIC STEM CELLS; GENOMICS; MICE; PROMOTER REGIONS, GENETIC; SEQUENCE ANALYSIS, DNA; SOFTWARE; TRANSCRIPTION FACTORS;

EID: 84897727307     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btt585     Document Type: Article

References (37)

1. Arnold,P. et al. (2011)MotEvo: integrated bayesian probabilistic methods for inferring regulatory sites and motifs on multiple alignments of DNA sequences. Bioinformatics, 28, 487-494.
2. Berger,M. et al. (2006) Compact, universal DNA microarrays to comprehensively determine transcription-factor binding site specificities. Nat. Biotechnol., 24, 1429-1435.
3. Chen,X. et al. (2008) Integration of external signaling pathways with the core transcriptional network in embryonic stem cells. Cell, 133, 1106-1117.
4. Djordjevic,M. et al. (2003) A biophysical approach to transcription factor binding site discovery. Genome Res., 13, 2381-2390.
5. Ernst,J. et al. (2010) Integrating multiple evidence sources to predict transcription factor binding in the human genome. Genome Res., 20, 526-536.
6. Fidalgo,M. et al. (2011) Zfp281 functions as a transcriptional repressor for pluripotency of mouse embryonic stem cells. Stem Cells, 29, 1705-1716.
7. Foat,B. et al. (2006) Statistical mechanical modeling of genome-wide transcription factor occupancy data by matrixreduce. Bioinformatics, 22, e141-e149.
8. Fu,F. and Zhou,Q. (2013) Learning sparse causal gaussian networks with experimental intervention: regularization and coordinate descent. J. Am. Stat. Assoc., 108, 288-300.
9. Furuya,S. et al. (2008) Inactivation of the 3-phosphoglycerate dehydrogenase gene in mice: changes in gene expression and associated regulatory networks resulting from serine deficiency. Funct. Integr. Genomics, 8, 235-249.
10. Gu,P. et al. (2011) Differential recruitment of methyl CpG-binding domain factors and dna methyltransferases by the orphan receptor germ cell nuclear factor initiates the repression and silencing of oct4. Stem Cells, 29, 1041-1051.
11. Gupta,M. and Liu,J. (2003) Discovery of conserved sequence patterns using a stochastics dictionary model. J. Am. Stat. Assoc., 98, 55-66.
12. He,X. et al. (2009) A biophysical model for analysis of transcription factor interaction and binding site arrangement from genome-wide binding data. PLoS One, 4, e8155.
13. He,X. et al. (2010) Thermodynamics-based models of transcriptional regulation by enhancers: the roles of synergistic activation, cooperative binding and shortrange repression. PLoS Comput. Biol., 6, e1000935.
14. Herkert,B. and Eilers,M. (2010) Transcriptional repression: the dark side of myc. Genes Cancer, 1, 580-586.
15. Jessen,K. and Mirsky,R. (2008) Negative regulation of myelination: relevance for development, injury, and demyelinating disease. Glia, 56, 1552-1565.
16. Kaplan,N. et al. (2009) The DNA-encoded nucleosome organization of a eukaryotic genome. Nature, 458, 362-366.
17. Kaplan,T. et al. (2011) Quantitative models of the mechanisms that control genomewide patterns of transcription factor binding during early drosophila development. PLoS Genet., 7, e1001290.
18. Kerosuo,L. et al. (2008) Myc increases self-renewal in neural progenitor cells through miz-1. J. Cell Sci., 121, 3941-3950.
19. Kharchenko,P. et al. (2008) Design and analysis of chip-seq experiments for dnabinding proteins. Nat. Biotechnol., 26, 1351-1359.
20. Kim,J. et al. (2008) An extended transcriptional network for pluripotency of embryonic stem cells. Cell, 132, 1049-1061.
21. Laurila,K. et al. (2009) A protein-protein interaction guided method for competitive transcription factor binding improves target predictions. Nucleic Acids Res., 37, e146.
22. Marbach,D. et al. (2012) Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks. Genome Res., 22, 1334-1349.
23. Mason,M. et al. (2009) Signed weighted gene co-expression network analysis of transcriptional regulation in murine embryonic stem cells. BMC Genomics, 10, 327.
24. Mason,M. et al. (2010) Identification of context-dependent motifs by contrasting chip binding data. Bioinformatics, 26, 2826-2832.
25. Matys,V. et al. (2003) TRANSFAC: transcriptional regulation, from patterns to profiles. Nucleic Acids Res., 31, 374-378.
26. Morrish,F. et al. (2002) c-MYC apoptotic function is mediated by NRF-1 target genes. Gene Dev., 17, 240-255.
27. Narlikar,L. et al. (2007) A nucleosome-guided map of transcription factor binding sites in yeast. PLoS Comput. Biol., 3, e215.
28. Ramsey,S. et al. (2010) Genome-wide histone acetylation data improve prediction of mammalian transcription factor binding sites. Bioinformatics, 26, 2071-2075.
29. Raveh-Sadka,T. et al. (2009) Incorporating nucleosomes into thermodynamic models of transcription regulation. Genome Res., 19, 1480-1496.
30. Teif,V. and Rippe,K. (2010) Statistical-mechanical lattice models for protein-DNA binding in chromatin. J. Phys: Condens. Matter, 22, 414105-414118.
31. Verykokakis,M. et al. (2007) The RAS-dependent erf control of cell proliferation and differentiation is mediated by c-Myc repression. J. Biol. Chem., 282, 30285-30294.
32. Wang,J. et al. (2006) A protein interaction network for pluripotency of embryonic stem cells. Nature, 444, 364-368.
33. Wasson,T. and Hartemink,A. (2009) An ensemble model of competitive multifactor binding of the genome. Genome Res., 19, 2101-2112.
34. Won,K.-J. et al. (2010) Genome-wide prediction of transcription factor binding sites using an integrated model. Genome Biol., 11, R7.
35. Zhou,Q. (2010) On weight matrix and free energy models for sequence motif detection. J. Comput. Biol., 17, 1621-1638.
36. Zhou,Q. and Wong,W. (2004) CisModule: de novo discovery of cis-regulatory modules by hierarchical mixture modeling. Proc. Natl Acad. Sci. USA, 101, 12114-12119.
37. Zhou,Q. et al. (2007) A gene regulatory network in mouse embryonic stem cells. Proc. Natl Acad. Sci. USA, 104, 16438-443.