第6章

参考文献：第6章 染色质免疫共沉淀测序数据分析


李敏俐. 2010. ChIP技术及其在基因组水平上分析DNA与蛋白质相互作用. 遗传. 32(3): 219-228.

Barski, A., et al. 2007. High-resolution profiling of histone methylations in the human genome. Cell. 129(4): 823-837. [PubMed]

Boeva, V., et al. 2010. De novo motif identification improves the accuracy of predicting transcription factor binding sites in ChIP-Seq data analysis. Nucleic Acids Res. 38(11): e126. [PubMed]

Erlich, Y., et al. 2008. Alta-Cyclic: a self-optimizing base caller for next-generation sequencing. Nat Methods. 5(8): 679-682. [PubMed]

Fejes, A. P., et al. 2008. FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology. Bioinformatics. 24(15): 1729-1730. [PubMed]

Hower, V., et al. 2011. Shape-based peak identification for ChIP-Seq. BMC Bioinformatics. 12: 15. [PubMed]

Ji, H., et al. 2008. An integrated software system for analyzing ChIP-chip and ChIP-seq data. Nat Biotechnol. 26(11): 1293-1300. [PubMed]

Johnson, D. S., et al. 2007. Genome-wide mapping of in vivo protein-DNA interactions. Science. 316(5830): 1497-1502. [PubMed]

Jothi, R., et al. 2008. Genome-wide identification of in vivo protein-DNA binding sites from ChIP-Seq data. Nucleic Acids Res. 36(16): 5221-5231. [PubMed]

Laajala, T. D., et al. 2009. A practical comparison of methods for detecting transcription factor binding sites in ChIP-seq experiments. BMC Genomics. 10: 618. [PubMed]

Lan, X., et al. 2011. W-ChIPeaks: a comprehensive web application tool for processing ChIP-chip and ChIP-seq data. Bioinformatics. 27(3): 428-430. [PubMed]

Lun, D. S., et al. 2009. A blind deconvolution approach to high-resolution mapping of transcription factor binding sites from ChIP-seq data. Genome Biol. 10(12): R142. [PubMed]

Mardis, E. R. 2007. ChIP-seq: welcome to the new frontier. Nat Methods. 4(8): 613-614. [PubMed]

Mikkelsen, T. S., et al. 2007. Genome-wide maps of chromatin state in pluripotent and lineage-committed cells. Nature. 448(7153): 553-560. [PubMed]

Orlando, V., et al. 1997. Analysis of chromatin structure by in vivo formaldehyde cross-linking. Methods. 11(2): 205-214. [PubMed]

Park, P. J. 2009. ChIP-seq: advantages and challenges of a maturing technology. Nat Rev Genet. 10(10): 669-680. [PubMed]

Pepke, S., et al. 2009. Computation for ChIP-seq and RNA-seq studies. Nat Methods. 6(11 Suppl): S22-32. [PubMed]

Prill, R. J., et al. 2010. Towards a rigorous assessment of systems biology models: the DREAM3 challenges. PLoS One. 5(2): e9202. [PubMed]

Robertson, G., et al. 2007. Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing. Nat Methods. 4(8): 651-657. [PubMed]

Rougemont, J., et al. 2008. Probabilistic base calling of Solexa sequencing data. BMC Bioinformatics. 9: 431. [PubMed]

Rozowsky, J., et al. 2009. PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls. Nat Biotechnol. 27(1): 66-75. [PubMed]

Schmidt, D., et al. 2009. ChIP-seq: using high-throughput sequencing to discover protein-DNA interactions. Methods. 48(3): 240-248. [PubMed]

Szalkowski, A. M. and C. D. Schmid. 2011. Rapid innovation in ChIP-seq peak-calling algorithms is outdistancing benchmarking efforts. Brief Bioinform. 12(6): 626-633. [PubMed]

Valouev, A., et al. 2008. Genome-wide analysis of transcription factor binding sites based on ChIP-Seq data. Nat Methods. 5(9): 829-834. [PubMed]

Visel, A., et al. 2009. ChIP-seq accurately predicts tissue-specific activity of enhancers. Nature. 457(7231): 854-858. [PubMed]

Wilbanks, E. G. and M. T. Facciotti. 2010. Evaluation of algorithm performance in ChIP-seq peak detection. PLoS One. 5(7): e11471. [PubMed]

Zhang, Y., et al. 2008. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9(9): R137. [PubMed]