In silico prediction of yeast deletion phenotypes
Genet. mol. res. (Online)
;
5(1): 224-232, Mar. 31, 2006. tab, graf
Article
in English
| LILACS
| ID: lil-449130
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.
Full text:
Available
Index:
LILACS (Americas)
Main subject:
Phenotype
/
Yeasts
/
Algorithms
/
Gene Deletion
/
Genes, Fungal
Type of study:
Prognostic study
/
Risk factors
Limits:
Animals
Language:
English
Journal:
Genet. mol. res. (Online)
Journal subject:
Molecular Biology
/
Genetics
Year:
2006
Type:
Article
Affiliation country:
United States
Institution/Affiliation country:
North Carolina State University/US
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