BioNLP - Biomedical text mining

Recent revolutions has made rapid use of text mining in many different domains. A range of text mining applications in the biomedical literature has been described. One example is PubGene that combines biomedical text mining with network visualization as an Internet service. Another example, which uses ontologies with textmining is "GoPubMed.org". Semantic similarity has also been used by text-mining systems, namely, GOAnnotator.
BioNLP refers to text mining applied to texts and literature of the biomedical and molecular biology domain. It is a rather recent research field on the edge of natural language processing, bioinformatics, medical informatics and computational linguistics.

There is an increasing interest in text mining and information extraction strategies applied to the biomedical and molecular biology literature due to the increasing number of electronically available publications stored in databases such as PubMed.

Main uses of text mining

The main developments in this area have been related to the identification of biological entities (named entity recognition), such as protein and gene names in free text, the association of gene clusters obtained by microarray experiments with the biological context provided by the corresponding literature, automatic extraction of protein interactions and associations of proteins to functional concepts (e.g. gene ontology terms). Even the extraction of kinetic parameters from text or the subcellular location of proteins have been addressed by information extraction and text mining technology.

Examples of BioNLP applications

Chilibot - A tool for finding relationships between genes or gene products.
FABLE - A gene-centric text-mining search engine for MEDLINE
LitInspector - Gene and signal transduction pathway data mining in PubMed abstracts.
PubAnatomy - An interactive visual search engine that provides new ways to explore relationships among Medline literature, text mining results, anatomical structures, gene expression and other background information.