Issue 6, 2014

The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach

Abstract

With rapidly changing technology, prediction of candidate genes has become an indispensable task in recent years mainly in the field of biological research. The empirical methods for candidate gene prioritization that succors to explore the potential pathway between genetic determinants and complex diseases are highly cumbersome and labor intensive. In such a scenario predicting potential targets for a disease state through in silico approaches are of researcher's interest. The prodigious availability of protein interaction data coupled with gene annotation renders an ease in the accurate determination of disease specific candidate genes. In our work we have prioritized the cervix related cancer candidate genes by employing Csaba Ortutay and his co-workers approach of identifying the candidate genes through graph theoretical centrality measures and gene ontology. With the advantage of the human protein interaction data, cervical cancer gene sets and the ontological terms, we were able to predict 15 novel candidates for cervical carcinogenesis. The disease relevance of the anticipated candidate genes was corroborated through a literature survey. Also the presence of the drugs for these candidates was detected through Therapeutic Target Database (TTD) and DrugMap Central (DMC) which affirms that they may be endowed as potential drug targets for cervical cancer.

Graphical abstract: The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach

Supplementary files

Article information

Article type
Paper
Submitted
03 Jan 2014
Accepted
05 Feb 2014
First published
05 Feb 2014

Mol. BioSyst., 2014,10, 1450-1460

Author version available

The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach

V. Hindumathi, T. Kranthi, S. B. Rao and P. Manimaran, Mol. BioSyst., 2014, 10, 1450 DOI: 10.1039/C4MB00004H

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