Bio-IT gaining prominence in India

The Indian Biotechnology Sector is one of the fastest growing knowledge based sectors in India and is expected to play a key role in shaping the economy. There is a great opportunity in big data in this industry there is a need for bio-informatics. This is primarily because of big data, micro-array, dissimulation studies and handling large amount of samples that have to be managed, stored and shared.
Various researchers got together to speak on Bio - IT and Leveraging IT power to make affordable medicines at India Bio 2013 held in Bengaluru. Evidently, there is an integration of IT with biological research. "Data is exploding in the field of biotechnology and there is a great demand for analyzing them, thus creating a huge opportunity," stated Dr Kshitish Acharya, faculty Scientist, Institute of Bioinformatics and Applied Biotechnology (IBAB) & Founder & Director, Shodhaka Life Sciences Private Limited. IT has influenced biotechnology and bridged the void to help create solutions for data storage and analysis. "Bio-IT is widely used in diagnosis. The detailing we were missing in diagnosis using classical methods can be corrected using IT. Algorithms can be used to check genes that may be switched on or switched off. Protein interactions can be studied better, and cures for a particular disease can be searched for in lesser time," added research scholar Ananth P.
IT is also used extensively in pharmaceutical industries. Since experimental techniques are costly, IT today plays a huge role in sequence database, PFAM database, evolutionary information of domains and 3D structure of proteins. Speaking on his current research, Ananth said, "System biology is used to identify micro molecules in type 2 diabetes and its progression into other complications and computational structural biology is the other area. For instance, when you study the proteins and RNA in cholera, algorithms are used to analyze protein sequences to predict and visualize their 3d structure."

Saurabh G, research scholar at GanitLab, commented on what lays ahead, "The next generation of sequencing will include several terabytes of raw data that's generated from one machine in a single week. Data explosion will be solved with statistics." He added that data sequencing is not considered expensive but analyzing the sequenced data is.