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An Exploration of Mining Gene Expression Mentions and their Anatomical Locations from Biomedical Text

Gerner M., Nenadic, G., Bergman, C. M

In: Proceedings of the BioNLP 2010 Workshop: BioNLP 2010 Workshop; 15 Jul 2010-15 Jul 2010; Uppsala, Sweden. 2010.

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Abstract

Here we explore mining data on gene expres-sion from the biomedical literature and present Gene Expression Text Miner (GETM), a tool for extraction of information about the expression of genes and their ana-tomical locations from text. Provided with recognized gene mentions, GETM identifies mentions of anatomical locations and cell lines, and extracts text passages where au-thors discuss the expression of a particular gene in specific anatomical locations or cell lines. This enables the automatic construction of expression profiles for both genes and ana-tomical locations. Evaluated against a ma-nually extended version of the BioNLP '09 corpus, GETM achieved precision and recall levels of 58.8% and 23.8%, respectively. Ap-plication of GETM to MEDLINE and PubMed Central yielded over 700,000 gene expression mentions. This data set may be queried through a web interface, and should prove useful not only for researchers who are interested in the developmental regulation of specific genes of interest, but also for data-base curators aiming to create structured re-positories of gene expression information. The compiled tool, its source code, the ma-nually annotated evaluation corpus and a search query interface to the data set ex-tracted from MEDLINE and PubMed Cen-tral is available at http://getm-project.sourceforge.net/.

Bibliographic metadata

Type of resource:
Content type:
Type of conference contribution:
Publication date:
Conference title:
BioNLP 2010 Workshop
Conference venue:
Uppsala, Sweden
Conference start date:
2010-07-15
Conference end date:
2010-07-15
Abstract:
Here we explore mining data on gene expres-sion from the biomedical literature and present Gene Expression Text Miner (GETM), a tool for extraction of information about the expression of genes and their ana-tomical locations from text. Provided with recognized gene mentions, GETM identifies mentions of anatomical locations and cell lines, and extracts text passages where au-thors discuss the expression of a particular gene in specific anatomical locations or cell lines. This enables the automatic construction of expression profiles for both genes and ana-tomical locations. Evaluated against a ma-nually extended version of the BioNLP '09 corpus, GETM achieved precision and recall levels of 58.8% and 23.8%, respectively. Ap-plication of GETM to MEDLINE and PubMed Central yielded over 700,000 gene expression mentions. This data set may be queried through a web interface, and should prove useful not only for researchers who are interested in the developmental regulation of specific genes of interest, but also for data-base curators aiming to create structured re-positories of gene expression information. The compiled tool, its source code, the ma-nually annotated evaluation corpus and a search query interface to the data set ex-tracted from MEDLINE and PubMed Cen-tral is available at http://getm-project.sourceforge.net/.

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:113908
Created by:
Nenadic, Goran
Created:
28th January, 2011, 13:20:31
Last modified by:
Nenadic, Goran
Last modified:
28th January, 2011, 18:04:39