IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Web Mining for Protein-to-Protein Interaction Information

Web Mining for Protein-to-Protein Interaction Information
View Sample PDF
Author(s): Hsi-Chieh Lee (Yuan Ze University, Taiwan, and National Chengchi University, Taiwan), Szu-Wei Huang (Yuan Ze University, Taiwan)and Eldon Y. Li (National Chengchi University, Taiwan, and California Polytechnic State University, USA)
Copyright: 2007
Pages: 30
Source title: Advances in Electronic Business, Volume 2
Source Author(s)/Editor(s): Eldon Y. Li (National Chengchi University, Taiwan)and Timon C. Du (The Chinese University of Hong Kong, China)
DOI: 10.4018/978-1-59140-678-5.ch012

Purchase

View Web Mining for Protein-to-Protein Interaction Information on the publisher's website for pricing and purchasing information.

Abstract

This study proposes a mining system for finding protein-to-protein interaction literatures from the databases on the Internet. In this system, we search for discriminating words for protein-to-protein interaction by way of statistics and the results from literatures. A threshold is also evaluated to check if a given literature is related to protein-to-protein interactions. In addition, a keypage-based search mechanism is used to find related papers for protein-to-protein interactions from a given document. To expand the search space and ensure better performance of the system, mechanisms for protein name identification and databases for protein names are also developed. The system is designed with a web-based user interface and a job-dispatching kernel. Experiments are conducted and the results have been checked by a biomedical expert. The experimental results indicate that by using the proposed mining system, it is helpful for researchers to find protein-to-protein literatures from the overwhelming pieces of information available on the biomedical databases over the Internet.

Related Content

Emrah Arğın. © 2022. 16 pages.
Ebru Gülbuğ Erol, Mustafa Gülsün. © 2022. 17 pages.
Yeşim Şener. © 2022. 18 pages.
Salim Kurnaz, Deimantė Žilinskienė. © 2022. 20 pages.
Dorothea Maria Bowyer, Walid El Hamad, Ciorstan Smark, Greg Evan Jones, Claire Beattie, Ying Deng. © 2022. 29 pages.
Savas S. Ates, Vildan Durmaz. © 2022. 24 pages.
Nusret Erceylan, Gaye Atilla. © 2022. 20 pages.
Body Bottom