Motif identification method based on Gibbs sampling and genetic algorithm
| Autor: | Kefeng Wang, Xiaochun Sheng |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Computer Networks and Communications Computer science Population 02 engineering and technology 03 medical and health sciences symbols.namesake Gene expression Genetic algorithm 0202 electrical engineering electronic engineering information engineering education Regulation of gene expression education.field_of_study business.industry Quantitative Biology::Molecular Networks Pattern recognition Position weight matrix Quantitative Biology::Genomics ComputingMethodologies_PATTERNRECOGNITION 030104 developmental biology symbols 020201 artificial intelligence & image processing Artificial intelligence Motif (music) business Software Gibbs sampling |
| Zdroj: | Cluster Computing. 20:33-41 |
| ISSN: | 1573-7543 1386-7857 |
| Popis: | The regulation of gene expression is the key of organism genetic mechanism. Motif identification is an important step in constructing expression regulatory network. Based on Gibbs sampling method, this work constructed position weight matrix, thereby proposing motif recognition method based on genetic algorithm. Scoring function is defined to update the population and obtain the convergence matrix of position weight, achieving the identification of motifs with different length. Simulation and experimental data sets were utilized to verify the accuracy and execution time of the algorithm. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink