Digital technologies and programming capabilities have become central to scientific research. From neurobiologists designing mathematical models and computer simulations to understand how our brain learns and remembers things, to mathematicians delving into human DNA searching for answers to the world’s data storage problems, all researchers today need to use vast amounts of data, analyse it, and draw insights. And this requires a good understanding of statistics and programming.
Mohan Wani, director at the National Centre for Cell Sciences, says even if a student hates mathematics, he or she must take up basic statistics courses in their under-graduate programmes for a career in research. “Statistical tools are required to design one’s own experiments, as well as to understand others’. Also, it is easier to understand computation in future if one has a basic understanding of statistics,” he says.
Rajendra Joshi, head of the department of high performance computing (medical and bioinformatics application group) at the Centre for Development of Advanced Computing, says whether it is chemistry, life sciences or any other subject, the amount of data available is large, and it is not humanly possible to analyse it without high performing computers. “So, scientists today need to understand computing,” he says, and advises pure science students to take up online or offline courses in programming languages.
Even for computer engineering students, learning the ropes of a completely new subject may be life-changing. When Manish Gupta, professor at Dhirubhai Ambani Institute of Information and Communication Technology in Gandhinagar, Gujarat, asked a Bachelor’s student doing BTech in ICT to solve a problem related to HIV, hereceived a call from the student’s mother questioning why her son was being asked to solve a biology problem. The same student, says Gupta, went on to do a PhD in pure biology, and later found an excellent job as data scientist at Microsoft Research.
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Gupta himself has gone far beyond his early focus on mathematics. He is a part of the DNA Data Storage Alliance that was formed in 2020 by Illumina, Microsoft Research, Twist Bioscience, and Western Digital, which has the mission to create and promote an interoperable storage ecosystem based on DNA as a data storage medium. “DNA in each of us stores life’s data in the most efficient way. In our lab, we try to find ways to store and retrieve digital data in DNA in the best and easiest possible way. Similarly, research students must be able to identify problems and then learn and use different types of information available to solve it, instead of sticking to just their domains,” he says.
Suhita Nadkarni, a neurobiologist at the Indian Institute of Science Education and Research, Pune, studies molecular principles underlying how the brain learns and remembers things. She says this requires replicating and simulating how the neurons transmit information and how the brain stores them. “For that, we have to design various algorithms and mathematical models. So, programming has become a life skill in all kinds of research,” she says.
Nadkarni’s fellow neurobiologist Collins Assisi says that institutes like IISER have made it compulsory for students to study all subjects in the first three semesters, which includes a course in programming, before choosing a specialisation later. Traditional universities too are taking steps in that direction. Ramanathan TV, head of the statistics department at Savitribai Phule Pune University, says that due to the demand for a bridge course for pure science students in data crunching, the department came up with a two-credit course specific to their field, three years ago.