A cross-genomic approach for systematic mapping of phenotypic traits to genes. Author Kam Jim, Kush Parmar, Mona Singh, Saeed Tavazoie Publication Year 2004 Type Journal Article Abstract We present a computational method for de novo identification of gene function using only cross-organismal distribution of phenotypic traits. Our approach assumes that proteins necessary for a set of phenotypic traits are preferentially conserved among organisms that share those traits. This method combines organism-to-phenotype associations,along with phylogenetic profiles,to identify proteins that have high propensities for the query phenotype; it does not require the use of any functional annotations for any proteins. We first present the statistical foundations of this approach and then apply it to a range of phenotypes to assess how its performance depends on the frequency and specificity of the phenotype. Our analysis shows that statistically significant associations are possible as long as the phenotype is neither extremely rare nor extremely common; results on the flagella,pili, thermophily,and respiratory tract tropism phenotypes suggest that reliable associations can be inferred when the phenotype does not arise from many alternate mechanisms. Keywords Escherichia coli, Models, Genetic, Phenotype, Chromosome Mapping, Bacterial Proteins, Genes, Bacterial, Pseudomonas aeruginosa, Fimbriae, Bacterial, Eubacterium, Flagellin, Genome, Bacterial, Respiratory System, Streptococcus pneumoniae, Tropism Journal Genome Res Volume 14 Issue 1 Pages 109-15 Date Published 01/2004 Alternate Journal Genome Res. Google ScholarBibTeXEndNote X3 XML