Algorithms and statistics are now at the core of research

Digital Technologies and programming skills have become a central part of scientific research. From neurobiologists designing mathematical models and computer simulations to understand how our brain learns and remembers things, to mathematicians studying human DNA looking for answers to the world’s data storage problems, all researchers today face huge challenges Use datasets, analyze and plot insights. And this requires a good understanding of statistics and programming.
Mohan Wani, director at the National Center for Cell Sciences, says even if a student hates math, he or she must take basic statistics courses in their undergraduate programs to begin a career in research. “Statistical tools are required to design your own experiments and to understand those of others. Also, in the future it will be easier to understand calculations if you have a basic understanding of statistics,” he says.
Rajendra Joshi, head of the Department of High Performance Computing (Medical and Bioinformatics Applications Group) at the Center for Development of Advanced Computing, says whether it’s chemistry, life sciences or another subject, the amount of data available is vast, and it’s humanly possible to analyze them without powerful computers. “So today scientists need to understand computers,” he says, advising pure science students to take online or offline courses in programming languages.
Even for computer science students, learning the basics of an entirely new subject can be life-changing. When Manish Gupta, a professor at the Dhirubhai Ambani Institute of Information and Communication Technology in Gandhinagar, Gujarat, asked an undergraduate student studying BTech in ICT to solve a problem related to HIV, he received a phone call from the student’s mother , in which she asked why her son was being asked to solve a biological problem. That same student, Gupta says, went on to earn a PhD in pure biology and later found a stellar job as a data scientist at Microsoft Research.

Gupta himself has gone well beyond his early focus on mathematics. It is part of the DNA Data Storage Alliance, formed in 2020 by Illumina, Microsoft Research, Twist Bioscience and Western Digital with the mission to create and promote an interoperable storage ecosystem based on DNA as a data storage medium. “The DNA in each of us stores life 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 way possible. Similarly, research students need to be able to identify problems and then learn and use different types of available information to solve them, rather than just being limited to their domains,” he says.
Suhita Nadkarni, a neurobiologist at the Indian Institute of Science Education and Research, Pune, studies molecular principles underlying brain learning and memory. She says this needs to be replicated and simulated, how the neurons transmit information and how the brain stores it. “For this we have to design different algorithms and mathematical models. So coding has become a life skill in all types of research,” she says.
Nadkarni’s colleague neurobiologist Collins Assisi says institutes like IISER require students to study all subjects, including programming, for the first three semesters before later deciding on a specialization. Traditional universities are also taking steps in this direction. Ramanathan TV, head of the statistics department at Savitribai Phule Pune University, says that due to demand for a bridge course for pure science students in data crunching three years ago, the department developed a two-credit course specific to their field.

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