title: Enriching for direct regulatory targets in perturbed gene-expression profiles.
abstract: Here we build on a previously proposed algorithm to infer direct regulatory relationships using gene-expression profiles from cells in which individual genes are deleted or overexpressed. The updated algorithm can process networks containing feedback loops, incorporate positive and negative regulatory relationships during network reconstruction, and utilize data from double mutants to resolve ambiguous regulatory relationships. When applied to experimental data the reconstruction procedure preferentially retains direct transcription factor-target relationships.
authors.affiliation: Department of Molecular Genetics and Microbiology, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA.
authors.forename: Susannah G
authors.initials: SG
authors.lastname: Tringe
authors.forename: Andreas
authors.initials: A
authors.lastname: Wagner
authors.forename: Stephanie W
authors.initials: SW
authors.lastname: Ruby
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D019295:Computational Biology / Q000379:methods; D003196:Computer Graphics; D003198:Computer Simulation; D004271:DNA, Fungal / Q000235:genetics; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D015966:Gene Expression Regulation, Fungal / Q000235:genetics*; D009154:Mutation / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012045:Regulatory Sequences, Nucleic Acid / Q000235:genetics*; D012441:Saccharomyces cerevisiae / Q000235:genetics
chemical_list: D004271:DNA, Fungal