Literature DB >> 15509599

MedKit: a helper toolkit for automatic mining of MEDLINE/PubMed citations.

Jing Ding1, Daniel Berleant.   

Abstract

UNLABELLED: MEDLINE/PubMed is one of the most important information sources for bioinformatics text mining. However, there remain limitations in working with MEDLINE/PubMed citations. For example, PubMed imposes an upper limit of 10,000 for downloading PMID list or citations; and MEDLINE files are too large for most off-the-shelf XML parsers. We developed a Java package, MedKit, to work-around the limitations, as well as provide other useful functionalities, e.g. random sampling. Its four modules (querier, sampler, fetcher and parser) can work independently, or be pipelined in various combinations. It can be used as a stand-alone GUI application, or integrated into other text-mining systems. Text mining researchers and others may download and use the toolkit free for non-commercial purposes. AVAILABILITY: http://metnetdb.gdcb.iastate.edu/medkit CONTACT: berleant@iastate.edu.

Mesh:

Year:  2004        PMID: 15509599     DOI: 10.1093/bioinformatics/bti087

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  4 in total

1.  PubFocus: semantic MEDLINE/PubMed citations analytics through integration of controlled biomedical dictionaries and ranking algorithm.

Authors:  Maksim V Plikus; Zina Zhang; Cheng-Ming Chuong
Journal:  BMC Bioinformatics       Date:  2006-10-02       Impact factor: 3.307

2.  Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.

Authors:  Anthony Deeter; Mark Dalman; Joseph Haddad; Zhong-Hui Duan
Journal:  PLoS One       Date:  2017-10-19       Impact factor: 3.240

3.  PubMed QUEST: the PubMed query search tool. an informatics tool to aid cancer centers and cancer investigators in searching the PubMed databases.

Authors:  David A Hanauer; Arul M Chinnaiyan
Journal:  Cancer Inform       Date:  2007-02-12

4.  Genome bioinformatic analysis of nonsynonymous SNPs.

Authors:  David F Burke; Catherine L Worth; Eva-Maria Priego; Tammy Cheng; Luc J Smink; John A Todd; Tom L Blundell
Journal:  BMC Bioinformatics       Date:  2007-08-20       Impact factor: 3.169

  4 in total

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