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Computational solutions for omics data

Author(s): Berger, B; Peng, J; Singh, Mona

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Abstract: High-throughput experimental technologies are generating increasingly massive and complex genomic data sets. The sheer enormity and heterogeneity of these data threaten to make the arising problems computationally infeasible. Fortunately, powerful algorithmic techniques lead to software that can answer important biomedical questions in practice. In this Review, we sample the algorithmic landscape, focusing on state-of-the-art techniques, the understanding of which will aid the bench biologist in analysing omics data. We spotlight specific examples that have facilitated and enriched analyses of sequence, transcriptomic and network data sets.
Publication Date: 18-Apr-2013
Electronic Publication Date: 18-Apr-2013
Citation: Berger, B, Peng, J, Singh, M. (2013). Computational solutions for omics data. Nature Reviews Genetics, 14 (333 - 346. doi:10.1038/nrg3433
DOI: doi:10.1038/nrg3433
Pages: 333 - 346
Type of Material: Journal Article
Journal/Proceeding Title: Nature Reviews Genetics
Version: Author's manuscript

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