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pGenN, a Gene Normalization Tool for Plant Genes and Proteins in Scientific Literature
Author(s) -
Ruoyao Ding,
Cecilia Arighi,
JungYoun Lee,
Cathy Wu,
K. VijayShanker
Publication year - 2015
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0135305
Subject(s) - normalization (sociology) , gene nomenclature , computer science , annotation , information retrieval , gene annotation , heuristics , gene , named entity recognition , computational biology , natural language processing , data mining , database , bioinformatics , artificial intelligence , genome , biology , genetics , taxonomy (biology) , botany , management , sociology , anthropology , nomenclature , economics , task (project management) , operating system
Background Automatically detecting gene/protein names in the literature and connecting them to databases records, also known as gene normalization, provides a means to structure the information buried in free-text literature. Gene normalization is critical for improving the coverage of annotation in the databases, and is an essential component of many text mining systems and database curation pipelines. Methods In this manuscript, we describe a gene normalization system specifically tailored for plant species, called pGenN ( p ivot-based Gen e N ormalization). The system consists of three steps: dictionary-based gene mention detection, species assignment, and intra species normalization. We have developed new heuristics to improve each of these phases. Results We evaluated the performance of pGenN on an in-house expertly annotated corpus consisting of 104 plant relevant abstracts. Our system achieved an F-value of 88.9% (Precision 90.9% and Recall 87.2%) on this corpus, outperforming state-of-art systems presented in BioCreative III. We have processed over 440,000 plant-related Medline abstracts using pGenN. The gene normalization results are stored in a local database for direct query from the pGenN web interface (proteininformationresource.org/pgenn/). The annotated literature corpus is also publicly available through the PIR text mining portal (proteininformationresource.org/iprolink/).

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