Network Embedding the Protein-Protein Interaction Network for Human Essential Genes Identification.

ABSTRACT: Essential genes are a group of genes that are indispensable for cell survival and cell fertility. Studying human essential genes helps scientists reveal the underlying biological mechanisms of a human cell but also guides disease treatment. Recently, the publication of human essential gene data makes it possible for researchers to train a machine-learning classifier by using some features of the known human essential genes and to use the classifier to predict new human essential genes. Previous studies have found that the essentiality of genes closely relates to their properties in the protein-protein interaction (PPI) network. In this work, we propose a novel supervised method to predict human essential genes by network embedding the PPI network. Our approach implements a bias random walk

SUBMITTER: Dai W 

PROVIDER: S-EPMC7074227 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature