Mining of Correlated Rules in Genome Sequences

Author

L. Lin
L. Wong
Tze-Yun LEONG, Singapore Management UniversityFollow
P. S. Lai

Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

11-2002

Abstract

With the huge amount of data collected by scientists in the molecular genetics community in recent years, there exists a need to develop some novel algorithms based on existing data mining techniques to discover useful information from genome databases. We propose an algorithm that integrates the statistical method, association rule mining, and classification rule mining in the discovery of allelic combinations of genes that are peculiar to certain phenotypes of diseased patients.

Discipline

Computer Sciences | Databases and Information Systems | Genetics and Genomics | Health Information Technology | Numerical Analysis and Scientific Computing | Theory and Algorithms

Publication

American Medical Informatics Association Annual Symposium Proceedings

First Page

1084

Last Page

1084

ISBN

9781560536000

Publisher

Hanley and Belfus

City or Country

Philadelphia, PA

Citation

Lin, L.; Wong, L.; Tze-Yun LEONG; and Lai, P. S.. Mining of Correlated Rules in Genome Sequences. (2002). American Medical Informatics Association Annual Symposium Proceedings. 1084-1084.
Available at: https://ink.library.smu.edu.sg/sis_research/3061

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Additional URL

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2244572/