MedlineR: an open source library in R for Medline literature data mining.
CONCLUSIONS
We describe an open source library written in the R programming language for Medline literature data mining. This MedlineR library includes programs to query Medline through the NCBI PubMed database; to construct the co-occurrence matrix; and to visualize the network topology of query terms. The open source nature of this library allows users to extend it freely in the statistical programming language of R. To demonstrate its utility, we have built an application to analyze term-association by using only 10 lines of code. We provide MedlineR as a library foundation for bioinformaticians and statisticians to build more sophisticated literature data mining applications.


BACKGROUND
The library is available from http://dbsr.duke.edu/pub/MedlineR.
Duke Comprehensive Cancer Center, Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC 27710, USA. Lin00025@mc.duke.edu <Lin00025@mc.duke.edu>
Simon M
SM
Lin
Patrick
P
McConnell
Kimberly F
KF
Johnson
Jennifer
J
Shoemaker
D000043:Abstracting and Indexing / Q000379:methods; D003628:Database Management Systems; D005786:Gene Expression Regulation / Q000502:physiology*; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D007990:Libraries; D016239:MEDLINE; D008954:Models, Biological; D009323:Natural Language Processing; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D010363:Pattern Recognition, Automated; D010506:Periodicals as Topic; D040901:Proteomics / Q000379:methods; D015398:Signal Transduction / Q000502:physiology*; D012984:Software; D014584:User-Computer Interface