Predicting Novel Human Gene Ontology Annotations Using Semantic Analysis

—The correct interpretation of many molecular biology experiments depends in an essential way on the accuracy and consistency of the existing annotation databases. Such databases are meant to act as repositories for our biological knowledge as we acquire and refine it. Hence, by definition, they are incomplete at any given time. In this paper, we describe a technique that improves our previous method for predicting novel GO annotations by extracting implicit semantic relationships between genes and functions. In this work, we use a vector space model and a number of weighting schemes in addition to our previous latent semantic indexing approach. The technique described here is able to take into consideration the hierarchical structure of the Gene Ontology (GO) and can weight differently GO terms situated at different depths. The prediction abilities of 15 different weighting schemes are compared and evaluated. Nine such schemes were previously used in other problem domains, while six...

• Type: Journal
• Year: 2010
• Where: TCBB
• Authors: Bogdan Done, Purvesh Khatri, Arina Done, Sorin Draghici
• Keywords: Annotations, N2tn Weighting Scheme, TCBB 2010, Weighting Scheme