Insilico Identification of Disease Genes using Microarray Data and Protein-Protein Interaction Networks.

Date of Submission

December 2015

Date of Award

Winter 12-12-2016

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Computer Science


Machine Intelligence Unit (MIU-Kolkata)


Maji, Pradipta (MIU-Kolkata; ISI)

Abstract (Summary of the Work)

One of the important problems in functional genomics is how to select the disease genes. In this regard, the paper presents a new similarity measure to compute the functional similarity between two genes. It is based on the information of protein-protein interaction networks. A new gene selection algorithm is introduced to identify disease genes, integrating judiciously the information of gene expression profiles and protein-protein interaction networks. The proposed algorithm selects a set of genes from microarray data as disease genes by maximizing the relevance and functional similarity of the selected genes. The performance of the proposed algorithm, along with a comparison with other related methods, is demonstrated on colorectal cancer data set.


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Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.


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