title: The ForeSee (4C) approach for integrative analysis in gene discovery.
abstract: The development of high-throughput experimental techniques has made measurements for virtually all kinds of cellular components possible. Effective integration and analysis of this diverged information to produce insightful knowledge is central to biological study today. In this chapter, we present a methodology for building integrative analytical workbenches using the workflow technology. We focus on the field of gene discovery through the combined study of transcriptomics, genomics and epigenomics, although the methodology is generally applicable to any omics-data analysis for biomarker discovery. We illustrate the application of the methodology by presenting our study on the identification of aberrant genomic regions, genes and/or their regulatory elements with their implications for breast cancer research. We also discuss the challenges and opportunities brought by the latest development of the next generation sequencing technology.
authors.affiliation: Department of Computing, Imperial College London, London, UK. y.guo@imperial.ac.uk
authors.forename: Yike
authors.initials: Y
authors.lastname: Guo
authors.forename: Robin E J
authors.initials: RE
authors.lastname: Munro
authors.forename: Dimitrios
authors.initials: D
authors.lastname: Kalaitzopoulos
authors.forename: Anita
authors.initials: A
authors.lastname: Grigoriadis
mesh_terms: D057890:Epigenomics; D020869:Gene Expression Profiling; D056726:Genetic Association Studies / Q000379:methods*; D023281:Genomics; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans