Abstract
Functional genomics experiments and analyses give rise to large sets of results, each typically quantifying the relation of molecular entities including genes, gene products, polymorphisms, and other genomic features with biological characteristics or processes. There is tremendous utility and value in using these data in an integrative fashion to find convergent evidence for the role of genes in various processes, to identify functionally similar molecular entities, or to compare processes based on their genomic correlates. However, these gene-centered data are often deposited in diverse and non-interoperable stores. Therefore, integration requires biologists to implement computational algorithms and harmonization of gene identifiers both within and across species. The GeneWeaver web-based software system brings together a large data archive from diverse functional genomics data with a suite of combinatorial tools in an interactive environment. Account management features allow data and results to be shared among user-defined groups. Users can retrieve curated gene set data, upload, store, and share their own experimental results and perform integrative analyses including novel algorithmic approaches for set–set integration of genes and functions.
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Jay, J.J., Chesler, E.J. (2014). Performing Integrative Functional Genomics Analysis in GeneWeaver.org. In: Ochs, M. (eds) Gene Function Analysis. Methods in Molecular Biology, vol 1101. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-721-1_2
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DOI: https://doi.org/10.1007/978-1-62703-721-1_2
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