title: Modeling genomic regulatory networks with big data.
abstract: High-throughput sequencing, large-scale data generation projects, and web-based cloud computing are changing how computational biology is performed, who performs it, and what biological insights it can deliver. I review here the latest developments in available data, methods, and software, focusing on the modeling and analysis of the gene regulatory interactions in cells. Three key findings are: (i) although sophisticated computational resources are increasingly available to bench biologists, tailored ongoing education is necessary to avoid the erroneous use of these resources. (ii) Current models of the regulation of gene expression are far too simplistic and need updating. (iii) Integrative computational analysis of large-scale datasets is becoming a fundamental component of molecular biology. I discuss current and near-term opportunities and challenges related to these three points.
authors.affiliation: Division of Human Biology, Fred Hutchinson Cancer Research Center (FHCRC), 1100 Fairview Avenue North, PO Box 19024, Seattle, WA 98109, USA. Electronic address: HBolouri@fhcrc.org.
authors.forename: Hamid
authors.initials: H
authors.lastname: Bolouri
mesh_terms: D000818:Animals; D030541:Databases, Genetic; D004194:Disease / Q000235:genetics; D053263:Gene Regulatory Networks / Q000235:genetics*; D016678:Genome / Q000235:genetics*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008957:Models, Genetic
keywords: big data; bioinformatics; computational biology; gene regulatory networks; modeling; network biology; systems biology