Biomedical text mining

Biomedical text mining

Biomedical text mining (also known as BioNLP) refers to text mining applied to texts and literature of the biomedical and molecular biology domain. Itis 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 applications

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 systems.


* [ XTractor] - Discovering Newer Scientific Relations Across PubMed Abstracts. A tool to obtain manually annotated relationships for Proteins, Diseases, Drugs and Biological Processes as they get published in PubMed.
* [ Chilibot] : A tool for finding relationships between genes or gene products.
* [ Information Hyperlinked Over Proteins (iHOP)] (ref.: [ Bioinformatics, 2005 Sep 1;21 Suppl 2:ii252-ii258.] ): "A network of concurring genes and proteins extends through the scientific literature touching on phenotypes, pathologies and gene function. iHOP provides this network as a natural way of accessing millions of PubMed abstracts. By using genes and proteins as hyperlinks between sentences and abstracts, the information in PubMed can be converted into one navigable resource, bringing all advantages of the internet to scientific literature research."
* [ FABLE] : A gene-centric text-mining search engine for MEDLINE
* [ GoPubMed] : retrieves PubMed abstracts for your search query, then detects ontology terms from the Gene Ontology and Medical Subject Headings in the abstracts and allows the user to browse the search results by exploring the ontologies and displaying only papers mentioning selected terms, their synonyms or descendants.
* [ LitInspector] - Gene and signal transduction pathway data mining in PubMed abstracts.
* [ PubGene] - Co-occurrence networks display of gene and protein symbols as well as MeSH, GO, PubChem and interaction terms (such as "binds" or "induces") as these appear in MEDLINE records (that is, PubMed titles and abstracts).


* [ Text-mining and information-retrieval services for molecular biology]
* [ Text mining for metabolic pathways, signaling cascades, and protein networks]
* [ Text-mining approaches in molecular biology and biomedicine]
* [ Biomedical LIterature Mining Publications (BLIMP)] : A comprehensive and regularly updated index of publications on (bio)medical text mining

Conferences at which BioNLP research is presented

BioNLP is presented at a variety of meetings:

* Pacific Symposium on Biocomputing: in plenary session
* Intelligent Systems for Molecular Biology: in plenary session and also in the BioLINK and Bio-ontologies workshops
* Association for Computational Linguistics and North American Association for Computational Linguistics annual meetings and associated workshops: in plenary session and as part of the BioNLP workshop (see below)
* [ BioNLP 2008]
* American Medical Informatics Association annual meeting: in plenary session

See also

* BioCreative
* TREC Genomics

External links

* [ The BioNLP mailing list archives]
* [ Corpora for biomedical text mining]
* [ The BioCreative evaluations of biomedical text mining technologies]
* [ Directory of people involved in BioNLP]

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