Biomedical subjects

Oliver D King

Publications and source records attributed to Oliver D King.

4 recordsLinked to original sources

PubMed2003

A non-parametric model for transcription factor binding sites.

We introduce a non-parametric representation of transcription factor binding sites which can model arbitrary dependencies between positions. As two parameters are varied, this representation smoothly interpolates between the empirical distribution of binding sites and the standard position-specific scoring matrix (PSSM). In a test of generalization to unseen binding sites using 10-fold cross-validation on known binding sites for 95 TRANSFAC transcription factors, this representation outperforms PSSMs on between 65 and 89 of the 95 transcription factors, depending on the choice of the two adjustable parameters. We also discuss how the non- parametric representation may be incorporated into frameworks for finding binding sites given only a collection of unaligned promoter regions.

Base Sequence↗

PubMed2003

Predicting gene function from patterns of annotation.

The Gene Ontology (GO) Consortium has produced a controlled vocabulary for annotation of gene function that is used in many organism-specific gene annotation databases. This allows the prediction of gene function based on patterns of annotation. For example, if annotations for two attributes tend to occur together in a database, then a gene holding one attribute is likely to hold the other as well. We modeled the relationships among GO attributes with decision trees and Bayesian networks, using the annotations in the Saccharomyces Genome Database (SGD) and in FlyBase as training data. We tested the models using cross-validation, and we manually assessed 100 gene-attribute associations that were predicted by the models but that were not present in the SGD or FlyBase databases. Of the 100 manually assessed associations, 41 were judged to be true, and another 42 were judged to be plausible.

Animals↗

PubMed2003

GoFish finds genes with combinations of Gene Ontology attributes.

SUMMARY: GoFish is a Java application that allows users to search for gene products with particular gene ontology (GO) attributes, or combinations of attributes. GoFish ranks gene products by the degree to which they satisfy a Boolean query. Four organisms are currently supported: Saccaromyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and M.musculus.

Amino Acid Sequence↗

PubMed2003

Predicting phenotype from patterns of annotation.

MOTIVATION: Predicting the outcome of specific experiments (such as the growth of a particular mutant strain in a particular medium) has the potential to allow researchers to devote resources to experiments with higher expected numbers of 'hits'. RESULTS: We use decision trees to predict phenotypes associated with Saccharomyces cerevisiae genes on the basis of Gene Ontology (GO) functional annotations from the Saccharomyces Genome Database (SGD) and other phenotypic annotations from the Yeast Phenotype Catalog at the Munich Information Center for Protein Sequences (MIPS). We assess the methodology in three ways: (1) we use cross-validation on the phenotypic annotations listed in MIPS, and show ROC curves indicating the tradeoff between true-positive rate and false-positive rate; (2) we do a literature-search for 100 of the predicted gene-phenotype associations that are not listed in MIPS, and find evidence for 43 of them; (3) we use deletion strains to experimentally assess 61 predicted gene-phenotype associations not listed in MIPS; significantly more of these deletion strains show abnormal growth than would be expected by chance.

Algorithms↗