About us

The wide-spread availability of biological data types of various forms, such as genomic and medical data, has made the use of computational approaches both easier and more inevitable than ever before. Motivated by this need to solve important bio-medical problems using computational approaches, our group works on solving several interesting problems using data mining techniques.


* Dey et al's paper on A pattern mining based integrative framework for biomarker discovery accepted on ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM-BCB 2012), October 7-10, Orlando, FL, 2012.

* Fang et al's Modeling Kinetic Rate Variation in Third Generation DNA Sequencing Data to Detect Putative Modifications to DNA Bases , accepted in Genome Research, 2012.

* Fang et al's High-order SNP Combinations Associated with Complex Diseases: Efficient Discovery, Statistical Power and Functional Interactions, accepted in PLoS One, 2012.

* Fang et al's paper on mining low-support discriminative patterns, in IEEE TKDE as a regular paper, 2012.

* Atluri et al's paper on discovering coherent value bicliques in genetic interaction data, accepted at BIOKDD 2010.

* Fang et al's paper on subspace differential coexpression analysis accepted by PSB 2010.

* Pandey et al's paper on incorporating functional inter-relationships into protein function prediction algorithms accepted by BMC Bioinformatics.

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