Using Drosophila melanogaster Data to Discover Disease-Related Protein Interactions in Humans

Author

Costello, J.C. ; Buchanan-Carter, J.E. ; Dalkilic, Mehmet M. ; Andrews, Justen

Author_Institution

Sch. of Informatics, Indiana Univ., Bloomington, IN

fYear

2007

fDate

1-5 April 2007

Firstpage

469

Lastpage

475

Abstract

The discovery and understanding of functional relationships amongst genes and their gene products are fundamental to our understanding of human disease. Data regarding protein-protein interactions in humans are not complete and computational techniques along with data provided from other organisms can be used to better inform relationships in humans. We demonstrate the utility of using genome scale data from Drosophila melanogaster to predict protein-protein relationships for human proteins specific to disease. To find the most likely candidates for protein-protein interaction, the predicted relationships are tested against human protein interaction and known disease data, then ranked through a support vector machine. An illustrative example related to hBrm and hSNF5 shows the validity of our approach

Keywords

biology computing; diseases; genetics; proteins; support vector machines; Drosophila melanogaster data; disease-related protein interactions; human disease; protein-protein interaction; support vector machine; Bioinformatics; Computational biology; Computational intelligence; Fungi; Genetics; Genomics; Humans; Organisms; Parkinson´s disease; Proteins;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Bioinformatics and Computational Biology, 2007. CIBCB '07. IEEE Symposium on

Conference_Location

Honolulu, HI

Print_ISBN

1-4244-0710-9

Type

conf

DOI

10.1109/CIBCB.2007.4221257

Filename

4221257