title: The CRIT framework for identifying cross patterns in systems biology and application to chemogenomics.
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.
authors: Department of Genetics, 77 Ave. of Louis Pasteur, Harvard Medical School, Boston, MA 02115, USA.
authors: Tara A
authors: TA
authors: Gianoulis
authors: Ashish
authors: A
authors: Agarwal
authors: Michael
authors: M
authors: Snyder
authors: Mark B
authors: MB
authors: Gerstein
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D005786:Gene Expression Regulation; D059647:Gene-Environment Interaction; D010363:Pattern Recognition, Automated / Q000379:methods*; D010597:Pharmacogenetics / Q000379:methods*; D011485:Protein Binding; D060066:Protein Interaction Maps; D012045:Regulatory Sequences, Nucleic Acid; D013312:Stress, Physiological; D049490:Systems Biology; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D014157:Transcription Factors