title: Prediction of gene phenotypes based on GO and KEGG pathway enrichment scores.
abstract: Observing what phenotype the overexpression or knockdown of gene can cause is the basic method of investigating gene functions. Many advanced biotechnologies, such as RNAi, were developed to study the gene phenotype. But there are still many limitations. Besides the time and cost, the knockdown of some gene may be lethal which makes the observation of other phenotypes impossible. Due to ethical and technological reasons, the knockdown of genes in complex species, such as mammal, is extremely difficult. Thus, we proposed a new sequence-based computational method called kNNA-based method for gene phenotypes prediction. Different to the traditional sequence-based computational method, our method regards the multiphenotype as a whole network which can rank the possible phenotypes associated with the query protein and shows a more comprehensive view of the protein's biological effects. According to the prediction result of yeast, we also find some more related features, including GO and KEGG information, which are making more contributions in identifying protein phenotypes. This method can be applied in gene phenotype prediction in other species.
authors: Institute of Systems Biology, Shanghai University, 99 ShangDa Road, Shanghai 200444, China.
authors: Tao
authors: T
authors: Zhang
authors: Min
authors: M
authors: Jiang
authors: Lei
authors: L
authors: Chen
authors: Bing
authors: B
authors: Niu
authors: Yudong
authors: Y
authors: Cai
mesh_terms: D000465:Algorithms; D030541:Databases, Genetic; D055785:Gene Knockdown Techniques / Q000706:statistics & numerical data; D063990:Gene Ontology / Q000706:statistics & numerical data; D008957:Models, Genetic; D010641:Phenotype; D034622:RNA Interference; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000502:physiology; D029701:Saccharomyces cerevisiae Proteins / Q000235:genetics / Q000502:physiology
chemical_list: D029701:Saccharomyces cerevisiae Proteins