title: Cancer omics: from regulatory networks to clinical outcomes.
abstract: Current limitation in cancer genomic studies is a lack of the integration of various omics data generated through next generation sequencing technologies, as well as a lack of the sounding and comprehensive epigenomic and genomic information about a particular cancer cell type. In this review, we will discuss main aspects of current genomics research with its application in cancer topics. We will first overview the next-generation sequencing technologies, then outline the major computational approaches, particularly focusing on ChIP-based omics data, and list several remaining open questions facing computational biologists, further present regulatory network analysis inferred from the ChIP-based omics data; finally implicate the clinical outcomes from the network and pathway analysis.
authors.affiliation: Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA.
authors.forename: Binhua
authors.initials: B
authors.lastname: Tang
authors.forename: Pei-Yin
authors.initials: PY
authors.lastname: Hsu
authors.forename: Tim H-M
authors.initials: TH
authors.lastname: Huang
authors.forename: Victor X
authors.initials: VX
authors.lastname: Jin
mesh_terms: D000818:Animals; D014408:Biomarkers, Tumor / Q000235:genetics*; D019295:Computational Biology; D004252:DNA Mutational Analysis; D019143:Evolution, Molecular; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D020022:Genetic Predisposition to Disease; D005820:Genetic Testing; D015894:Genome, Human; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D009154:Mutation; D009369:Neoplasms / Q000175:diagnosis / Q000235:genetics* / Q000628:therapy; D010641:Phenotype; D057285:Precision Medicine; D011237:Predictive Value of Tests; D011379:Prognosis; D017422:Sequence Analysis, DNA; D018511:Systems Integration
chemical_list: D014408:Biomarkers, Tumor