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integrative genomics

Sunday 4 February 2007

Integrating results from diverse experiments is an essential process in our effort to understand the logic of complex systems, such as development, homeostasis and responses to the environment.

With the advent of high-throughput methods - including genome-wide association studies (GWAS), chromatin immunoprecipitation followed by sequencing (ChIP-seq) and RNA sequencing (RNA-seq) - acquisition of genome-scale data has never been easier.

Epigenomics, transcriptomics, proteomics and genomics each provide an insightful, and yet one-dimensional, view of genome function; integrative analysis promises a unified, global view.

However, the large amount of information and diverse technology platforms pose multiple challenges for data access and processing.

See also

- data integration
- data management
- next-generation genomics


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