Gene function prediction based on combining gene ontology hierarchy with multi-instance multi-label learning.

ABSTRACT: Gene function annotation is the main challenge in the post genome era, which is an important part of the genome annotation. The sequencing of the human genome project produces a whole genome data, providing abundant biological information for the study of gene function annotation. However, to obtain useful knowledge from a large amount of data, a potential strategy is to apply machine learning methods to mine these data and predict gene function. In this study, we improved multi-instance hierarchical clustering by using gene ontology hierarchy to annotate gene function, which combines gene ontology hierarchy with multi-instance multi-label learning frame structure. Then, we used multi-label support vector machine (MLSVM) and multi-label k-nearest neighbor (MLKNN) algorithm to predict the f

SUBMITTER: Li Z 

PROVIDER: S-EPMC9083914 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature