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In silico prediction of yeast deletion phenotypes
Soma Saha and Steffen Heber
Department of Computer Science, North Carolina State University, Raleigh, NC, USA
Corresponding author: S. Heber
E-mail: [email protected]
Genet. Mol. Res. 5 (1): 224-232 (2006)
Received January 10, 2006
Accepted February 17, 2006
Published March 31, 2006

ABSTRACT. Analysis of gene deletions is a fundamental approach for investigating gene function. We evaluated an algorithm that uses classification techniques to predict the phenotypic effects of gene deletions in yeast. We used a modified simulated annealing algorithm for feature selection and weighting. The selected features with high weights were phylogenetic conservation scores for bacteria, fungi (excluding Ascomycota), Ascomycota (excluding Saccharomyces cerevisiae), plants, and mammals, degree of paralogy, and number of protein-protein interactions. Classification was performed by weighted k-nearest neighbor and with support vector machine algorithms. To demonstrate how this approach might complement existing experimental procedures, we applied our algorithm to predict essential genes and genes causing morphological alterations in yeast.

Key words: Classification, Essential genes, Simulated annealing, Yeast, Phenotype

 

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