Classifying DNA repair genes by kernel-based support vector machines.

ABSTRACT: Human longevity is a complex phenotype that has a significant genetic predisposition. Like other biological processes, ageing process is governed through the regulation of signaling pathways and transcription factors. The DNA damage theory of ageing suggests that ageing is a consequence of un-repaired DNA damage accumulation. Intensive research has been carried out to elucidate the role of DNA repair systems in the ageing process. Decision Trees and Naive Bayesian Algorithm are two data-mining based classification methods for systematically analyzing data about human DNA repair genes. In this paper we develop a linearly combined kernel with Support Vector Machine (SVM) to analyze the ageing related data. The popular supervised learning algorithm enables better discrimination between ageing

SUBMITTER: Jiang H 

PROVIDER: S-EPMC3218421 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature