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Why is Big Data in Biology so big: Prof. Karthik Raman

Why is Big Data in Biology so big: Prof. Karthik Raman

Kiran Mazumdar-Shaw, executive chairperson of Biocon, while being conferred with an honorary Doctor of Philosophy degree in Biotechnology at Bennett University’s annual convocation, had said recently that while the first two decades of this century belonged to Information Technology, the world is now entering an era of Biology and Computational Science. Since several fields of the life sciences, such as Biology and Chemistry, presently rely on quantitative prediction and interpretation to address complex questions, where advanced statistical, computational and mathematical tools are used, Mazumdar-Shaw’s statement seems to be of increasing relevance in present-day times. Biologists may have huge amounts of data at their disposal but that needs substantive quantitative approaches to arrive at accurate analyses and interpretations.

“It is ironical that in a country like India where students are forced to make a choice between Mathematics and Biology right from class XII, there seems to be a plethora of options opening up in Biology and Computational Science with often an overlapping between the two,” says Karthik Raman, associate professor, Department of Biotechnology, IIT Madras (IIT-M) and coordinator for the institute’s Centre for Integrative Biology and Systems medicinE (IBSE).

Interdisciplinary influence

The pandemic, according to him, has accelerated the need for interdisciplinarity in education, since tech disruptions to make necessary predictions both in healthcare infrastructure and disease diagnosis are becoming increasingly important. Citing IIT-M’s dual degree programmes in Data Science, Biomedical Engineering and Computation Engineering, Raman explains that it is not uncommon for a mechanical engineering student under the programme to work with a faculty from the Biotechnology department on a master’s project that combines both knowledge of Biology and Computational Science. “Nearly 50% students enrolling for the interdisciplinary dual degree programme in Data Science tend to work on projects that have the significant application of Data Science in Biology. They can tailor their curriculum and course work to accumulate sufficient training in these two fields,” Raman adds.

IIT-M has also made it compulsory for all UG students to pursue an introductory course in Biology to expose students to the basic concepts of the subject. “It has elective modules such as ‘Big Data in Biology’ along with modules in Biomedical Engineering and Bio Energy to prepare students for careers in research and industry,” says Raman who teaches a course called Data Structures and Algorithms for Biology at IIT-M.

Career scope

“There are now a wide array of companies and startups that are solely focussed on developing the next generation of digital healthcare. Even the large technology and hardware organisations are building core competencies and dedicated teams in the domain. Such organisations are bringing several innovations in drug design, assisted living, disease prevention which require a large workforce having the skill sets that the students acquire. These can potentially be some rewarding destinations for the students after they graduate from the IIT,” says Mitali Mukerji, professor, Department of Bioscience and Bioengineering, IIT Jodhpur, where the emphasis has been given to core subjects like data structure and algorithm, ML, deep learning, and other areas of AI as part of a recent revamp of the UG, PG and PhD curriculum.

“Interestingly, these subjects are not only for the students of Computer Science but they are the core component of Bioscience and Bioengineering, Electrical Engineering, Civil Engineering, Mechanical Engineering, Metallurgical and Materials Engineering etc. On the other hand, the Bioscience and Bioengineering department of IIT Jodhpur has offered several courses related to Computational Biology, Bioinformatics, Multi-omics, System Biology, and Big Data analysis which covers the whole spectrum of Biology-Computational Science interface. Also, these subjects are not restricted to students with a Biology background, rather any student of other backgrounds can learn and contribute,” Mukerji adds.

With prospects in large pharma companies offering R&D positions and even startups providing technological solutions to biological problems opening up, graduates in such fields will have a wealth of opportunities, says Rajinder Singh Chauhan -dean, Research & Consultancy; HoD Biotechnology Department, Bennett University where a course on Computational Thinking & Programming is offered to Biotechnology students in the first semester itself. Additionally, from the third semester, a BTech Biotechnology student can take up a minor in Computer Science.

Relevant courses

Highlighting the need to pursue courses in Bioinformatics, Computational Biology, Python Programming, R programming, Chauhan elaborates, “We live in a world where the boundaries between disciplines are increasingly getting blurred. Experts in Computational Science and Biotechnology are now working hand in hand to provide solutions to problems in areas of medical sciences, ecology, evolutionary biology etc. For example, the vast amount of genome sequencing data that is getting generated all over the world from research labs working on various SARS-CoV-2 variants require algorithms developed through Computational Sciences for quick analysis.”

Abundant jobs

“Computational Science has become a vehicle for many fields to advance in terms of research and innovations. Advances in gene editing, drug discovery, genome mapping techniques have proved to be game-changers. As the outcomes of these technologies have a significant impact on human health and quality of life, so this field offers abundant jobs and stellar career growth,” explains Deepak Garg – Dean, International relations & Corporate Outreach; HOD, Computer Science & Engineering, Bennett University.

According to him, students can opt for Computer Science and Engineering and take elective/minor courses related to the biological sciences. “There are elective and open elective courses available on Computational Biology, Bioinformatics, Genomics etc. As the tools, software and technologies related to Biotechnology are becoming more modular and user-friendly, so specific domain knowledge requirements are becoming less rigorous. Some institutions also offer specialisations related to this, and there are many reputed universities that provide masters’ courses at the intersection of both,” Garg adds.

On whether the convergence of Computational Science and Biology will help students solve real-life problems, Priyadarshi Satpati, Department of Bioscience & Bioengineering, IIT Guwahati reveals, “The computers will reduce the cost and time for drug-discovery; machine learning can help understand the stage of disease by analysing images (example, brain scan data) while genome analysis will help personalised medicine in future. The opportunities are endless.”

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