Skip Navigation

This Article
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow FREE Full Text (Screen PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (4)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Palakal, M.
Right arrow Articles by Mishra, S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Palakal, M.
Right arrow Articles by Mishra, S.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Bioinformatics Vol. 18 no. 10 2002
Pages 1283-1288
© 2002 Oxford University Press


SAC 2002 Paper

An intelligent biological information management system

Mathew Palakal 1,*, Snehasis Mukhopadhyay 1, Javed Mostafa 2, Rajeev Raje 1, Mathias N'Cho 3 and Santosh Mishra 3

1 Computer Science Department, Indiana University Purdue University Indianapolis, Indianapolis, IN 46202, USA
2 School of Library and Information Science, Indiana University, Bloomington, IN 47405, USA
3 Bioinformatics Group, Eli Lilly & Co., Indianapolis, IN 46285, USA

Received on August 31, 2001 ; accepted on October 24, 2001

Motivation: As biomedical researchers are amassing a plethora of information in a variety of forms resulting from the advancements in biomedical research, there is a critical need for innovative information management and knowledge discovery tools to sift through these vast volumes of heterogeneous data and analysis tools. In this paper we present a general model for an information management system that is adaptable and scalable, followed by a detailed design and implementation of one component of the model. The prototype, called BioSifter, was applied to problems in the bioinformatics area.

Results: BioSifter was tested using 500 documents obtained from PubMed database on two biological problems related to genetic polymorphism and extracorporal shockwave lithotripsy. The results indicate that BioSifter is a powerful tool for biological researchers to automatically retrieve relevant text documents from biological literature based on their interest profile. The results also indicate that the first stage of information management process, i.e. data to information transformation, significantly reduces the size of the information space. The filtered data obtained through BioSifter is relevant as well as much smaller in dimension compared to all the retrieved data. This would in turn significantly reduce the complexity associated with the next level transformation, i.e. information to knowledge.

Contact: mpalakal{at}cs.iupui.edu

* To whom correspondence should be addressed.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
BioinformaticsHome page
A. Vailaya, P. Bluvas, R. Kincaid, A. Kuchinsky, M. Creech, and A. Adler
An architecture for biological information extraction and representation
Bioinformatics, February 15, 2005; 21(4): 430 - 438.
[Abstract] [Full Text] [PDF]



Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.