RMCL-ESA: A Novel Method to Detect Co-regulatory Functional Modules in Cancer
| Autor: | Jiawei Luo, Ying Yin |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Markov chain Computer science Scale (descriptive set theory) computer.software_genre Ovary cancer 03 medical and health sciences Identification (information) ComputingMethodologies_PATTERNRECOGNITION 030104 developmental biology Filter (video) Search algorithm Gene expression Data mining computer |
| Zdroj: | Intelligent Computing Theories and Application ISBN: 9783319959320 ICIC (2) |
| Popis: | Considering the increasingly large scale of gene expression data, common module identification algorithms exist many problems, such as large search space and long running time. A novel co-regulatory modules identification algorithm RMCL-ESA (Regularized Markov Cluster & Explosion Search Algorithm) based on improved Markov cluster and explosion search strategy has been proposed. Improved Markov cluster is adapted to preprocess gene expression profiles through three subprocedure: expansion, inflation, prune, which filter redundant genes and save computational cost. Then, two-stage explosion search strategy has been explored for identifying co-regulatory modules. Comparing with existing methods on breast cancer and ovary cancer datasets from TCGA, CRMs (Co-regulatory Functional Modules) of RMCL-ESA include more significant biological function GO-terms and regulation pathways with high enrichment score. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|