Prediction of Gene Phenotypes Based on GO and KEGG Pathway Enrichment Scores
Joint Authors
Zhang, Tao
Niu, B.
Chen, Lei
Jiang, Min
Cai, Yu-Dong
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-07
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Zhang, Tao& Jiang, Min& Chen, Lei& Niu, B.& Cai, Yu-Dong. 2013. Prediction of Gene Phenotypes Based on GO and KEGG Pathway Enrichment Scores. BioMed Research International،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1005316
Modern Language Association (MLA)
Zhang, Tao…[et al.]. Prediction of Gene Phenotypes Based on GO and KEGG Pathway Enrichment Scores. BioMed Research International No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-1005316
American Medical Association (AMA)
Zhang, Tao& Jiang, Min& Chen, Lei& Niu, B.& Cai, Yu-Dong. Prediction of Gene Phenotypes Based on GO and KEGG Pathway Enrichment Scores. BioMed Research International. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1005316
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1005316