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Big Data and Cancer Research

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Abstract

The advent of high-throughput technology has revolutionized biological sciences in the last two decades enabling experiments on the whole genome scale. Data from such large-scale experiments are interpreted at system’s level to understand the interplay among genome, transcriptome, epigenome, proteome, metabolome, and regulome.

Keywords

Single Tumor Cell Variant Call Format International Cancer Genome Consortium Cancer Genome Project Variant Call Format File 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgments

Research in Ganit Labs, Bio-IT Centre is funded by grants from the Government of India agencies (Department of Electronics and Information Technology; Department of Biotechnology; Department of Science and Technology; and the Council of Scientific and Industrial Research) and Department of Information Technology, Biotechnology and Science & Technology, Government of Karnataka, India. I thank Saurabh Gupta for helping in making Fig. 2, and Saurabh Gupta and Neeraja Krishnan for critically reading the manuscript. Ganit Labs is an initiative of Institute of Bioinformatics and Applied Biotechnology and Strand Life Sciences, both located in Bangalore, India.

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© Springer India 2016

Authors and Affiliations

  1. 1.Ganit Labs, Bio-IT CentreInstitute of Bioinformatics and Applied BiotechnologyBangaloreIndia

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