Identifying biological concepts from a protein-related corpus with a probabilistic topic model.

ABSTRACT:

Background

Biomedical literature, e.g., MEDLINE, contains a wealth of knowledge regarding functions of proteins. Major recurring biological concepts within such text corpora represent the domains of this body of knowledge. The goal of this research is to identify the major biological topics/concepts from a corpus of protein-related MEDLINE titles and abstracts by applying a probabilistic topic model.

Results

The latent Dirichlet allocation (LDA) model was applied to the corpus. Based on the Bayesian model selection, 300 major topics were extracted from the corpus. The majority of identified topics/concepts was found to be semantically coherent and most represented biological objects or concepts. The identified topics/concepts were further mapped to the controlled vocabulary

SUBMITTER: Zheng B 

PROVIDER: S-EPMC1420333 | biostudies-literature | 2006 Feb

REPOSITORIES: biostudies-literature