Genetic algorithm for assigning weights to gene expressions using functional annotations
| Autor: | Shubhra Sankar Ray, Sampa Misra |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Health Informatics Saccharomyces cerevisiae Correlation 03 medical and health sciences 0302 clinical medicine Gene Expression Regulation Fungal Genetic algorithm Cutoff Time point Data Curation Mathematics Electronic Data Processing Fitness function Models Genetic business.industry Pattern recognition Gene Expression Regulation Bacterial Gene Annotation Expression (mathematics) Computer Science Applications Weighting 030104 developmental biology Artificial intelligence Databases Nucleic Acid business Algorithms 030217 neurology & neurosurgery Bacillus subtilis |
| Zdroj: | Computers in Biology and Medicine. 104:149-162 |
| ISSN: | 0010-4825 |
| DOI: | 10.1016/j.compbiomed.2018.11.011 |
| Popis: | A method, named genetic algorithm for assigning weights to gene expressions using functional annotations (GAAWGEFA), is developed to assign proper weights to the gene expressions at each time point. The weights are estimated using functional annotations of the genes in a genetic algorithm framework. The method shows gene similarity in an improved manner as compared with other existing methods because it takes advantage of the existing functional annotations of the genes. The weight combination for the expressions at different time points is determined by maximizing the fitness function of GAAWGEFA in terms of the positive predictive value (PPV) for the top 10,000 gene pairs. The performance of the proposed method is primarily compared with Biweight mid correlation (BICOR) and original expression values for the six Saccharomyces cerevisiae datasets and one Bacillus subtilis dataset. The utility of GAAWGEFA is shown in predicting the functions of 48 unclassified genes (using p-value cutoff 10 − 13 ) from Saccharomyces cerevisiae microarray data where the expressions are weighted using GAAWGEFA and are clustered using k-medoids algorithm. The related code along with various parameters is available at http://sampa.droppages.com/GAAWGEFA.html . |
| Databáze: | OpenAIRE |
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