Abstract
Biological data is often tabular but finding statistically valid connections between entities in a sequence of tables can be problematic – for example, connecting particular entities in a drug property table to gene properties in a second table, using a third table associating genes with drugs. Here we present an approach (CRIT) to find connections such as these and show how it can be applied in a variety of genomic contexts including chemogenomics data.
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Citation
Tara A Gianoulis, Ashish Agarwal, Michael Snyder, and Mark Gerstein (2011). The CRIT framework for identifying cross patterns in systems biology and application to chemogenomics, Genome Biology 12(R32):1-12.
