The use of semantic similarity measures for optimally integrating heterogeneous Gene Ontology data from large scale annotation pipelines.

ABSTRACT: With the advancement of new high throughput sequencing technologies, there has been an increase in the number of genome sequencing projects worldwide, which has yielded complete genome sequences of human, animals and plants. Subsequently, several labs have focused on genome annotation, consisting of assigning functions to gene products, mostly using Gene Ontology (GO) terms. As a consequence, there is an increased heterogeneity in annotations across genomes due to different approaches used by different pipelines to infer these annotations and also due to the nature of the GO structure itself. This makes a curator's task difficult, even if they adhere to the established guidelines for assessing these protein annotations. Here we develop a genome-scale approach for integrating GO annotations

SUBMITTER: Mazandu GK 

PROVIDER: S-EPMC4123725 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature