Inferring biological tasks using Pareto analysis of high-dimensional data.
basic_science · Level V
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- Record sourced from PubMed, PMID 25622107.
- Also identified by DOI 10.1038/nmeth.3254.
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Abstract
We present the Pareto task inference method (ParTI; http://www.weizmann.ac.il/mcb/UriAlon/download/ParTI) for inferring biological tasks from high-dimensional biological data. Data are described as a polytope, and features maximally enriched closest to the vertices (or archetypes) allow identification of the tasks the vertices represent. We demonstrate that human breast tumors and mouse tissues are well described by tetrahedrons in gene expression space, with specific tumor types and biological functions enriched at each of the vertices, suggesting four key tasks.
Medical subject headings
- Computational Biology
- Data Interpretation, Statistical
- Gene Expression Profiling