The one who believes in mentorship beyond research
Dr Nita Parekh juggles physics and computational biology with ease, and has been instrumental in building the MTech course in bioinformatics at IIIT-H
By Disha Tandon
| Posted on January 13, 2025
How many people truly branch out from their PhD field? Probably, only a few. Dr Nita Parekh is one of them, having transitioned from physics to bioinformatics.
“In research, one often becomes deeply focused on a niche area… In India, most continue under the same guide, tackling similar problems all their lives,” says Parekh, adding that she has fully diversified from her PhD research.
“It was not easy. Writing papers and proposals for biology journals is a different world. In physics, I was recognised at conferences and was part of the Theoretical Physics Seminar Circuit, but in computational biology, I was an unknown,” she recalls.
Parekh holds a PhD in condensed matter physics from Jawaharlal Nehru University. Her journey took flight with three postdoctoral experiences that expanded her horizons beyond her original field. Her first postdoc in non-linear dynamics applied to chemical systems marked her initial steps away from condensed matter physics.
In 1997, she moved to the Centre for Cellular and Molecular Biology (CCMB) and joined the lab of Dr Somdutta Sinha, a fellow physicist, and a future lifelong mentor and friend. The two-year fellowship period was also significant on a personal front as Parekh became a mother.
At present, Parekh works as an Associate Professor in the Department of Computational Natural Sciences at the International Institute of Information Technology-Hyderabad (IIIT-H).
Lab Group Picture
Tryst with bioinformatics
Parekh joined iLabs, a private research company, as a domain expert in 2001, and simultaneously won the Senior Research Fellowship from the Council of Scientific and Industrial Research. This marked her initiation into bioinformatics, then in its early stages and ripe with promise as the Human Genome Project reached the public eye.
With limited experience in biology, Parekh immersed herself in literature on mass spectrometry, sequence analysis and protein structure. Her grounding in algorithms allowed her to quickly connect these complex topics, building a rare interdisciplinary skill set that would become invaluable.
Meanwhile, Dr Abhijit Mitra of IIIT-H was searching for an expert hand to help launch a bioinformatics programme, for which Dr Sinha recommended Parekh’s name. Therefore, by 2003, she was developing the curriculum for MTech in Bioinformatics at IIIT-H, setting a foundation for future students in this evolving discipline.
By 2005, Parekh secured a postdoctoral fellowship from the Department of Biotechnology, joining Dr Shekhar Mande’s team at the Centre for DNA Fingerprinting and Diagnostics (CDFD). However, IIIT-H was in no mood to let a gem like Parekh leave and invited her to teach a class once a week.
Parekh remembers how the field of bioinformatics was viewed with scepticism in the early years of her career. “It is a subject, just like physics, chemistry or biology!” she would insist. Yet, with only a limited range of specialisations available at that time and only a few trained in the field, bioinformatics was unfamiliar to many.
Building a curriculum
The journey to develop the bioinformatics curriculum was filled with challenges. Back in 2003, dedicated bioinformatics programmes were almost non-existent in the country. Certainly, no full-time degree programmes were running.
Parekh fondly mentions that one of her peers was amongst the first to receive a PhD in bioinformatics in India.
With her physics background, she focused on integrating algorithms and statistics into the curriculum. For certain specialised topics, she invited scientists from CDFD and CCMB to lecture. However, she soon realised that expertise in research did not always translate to effective teaching. As the curriculum evolved, so did her teaching approach, aiming at providing a comprehensive learning experience.
Most of the students who opt for a Master’s/PhD in computational natural sciences have a biology background, with limited skills in programming. They struggle with courses in programming, securing lower grades than their fellow classmates with a computer science background. Because of this reason, Parekh had encountered resistance against inclusion of a Shell scripting course during MTech curriculum revision cycles.
“They [students] cannot go to companies and do a PhD without scripting in bioinformatics,” Parekh says, adding that even a ‘C’ grade (minimum pass) would equip them to handle technical conversations and requirements in industry settings. This foundational knowledge in programming is essential for biologists to bridge the gap with software engineers.
Parekh also designed a course in next-generation sequencing, which directly boosted job prospects of students in pharmaceutical companies. “We have to update our curriculum according to what the industry demands,” she notes.
In India, computational natural sciences often face skepticism from traditional computer science fields. “This is a very narrow-minded outlook,” she states. “The computer science branch does not attract a lot of PhD students because they get a good job after BTech or MTech. To get a job in natural sciences, one has to do a PhD,” Parekh adds.
Academia vs industry
Anecdotal evidence suggests that the general mindset of the science faculties is that in research you are working for yourself, you are your own boss. Whereas, in an industry, you are working for someone else. Parekh feels this is a fallacy. “MTech students, especially those with loans, aim for industry jobs to ensure financial stability. Also, not everyone is suited for research,” she says.
Parekh articulates that for MTech students, particularly in fields like bioinformatics, industry aspirations lean toward biotech, health sciences and pharmaceuticals — not traditional IT. She stresses the importance of the institute’s support in securing relevant placements.
“If the institute is not going to help them, what will happen? Good students will stop coming and the programme will be affected.” She further emphasises that the deterioration of good programmes in such a specialised and indispensable field will eventually affect the overall research and tangible outputs.
However, she also highlights a common faculty approach where professors, eager for bright minds in their labs, often push students toward research and PhD paths. “I never liked this. Let students decide if they want to join me in my research.”
She always feels closer to her PhD students than to her peers, valuing the fresh perspective and sincerity young minds bring. “Young faculty and students do not talk politics, which is why I enjoy connecting with them,” she chuckles.
One of her former students, Sanchari Sircar recalls a moment of struggle with a paper revision. “I was ready to give up, but Nita ma’am sat with me, guiding me through each revision step.”
Research on COVID-19
Parekh’s research has lately focused on Artificial Intelligence (AI) assisted models for prediction of COVID-19 in patients. In today’s AI-driven world, where one-size-fits-all solutions often replace logical reasoning, Parekh’s approach stands out as a refreshing change.
“Chest radiograph image analysis was the first work using deep-learning models in my group. During this work, I realised that models can give very good results, but may not be explainable or generalisable on unseen data.”
Parekh insists that data imbalance is common in the field of biology, arising from the randomness of the biological processes. “We tried to understand the difference in the patterns manifested in the lungs due to COVID pneumonia compared to that due to pneumonia by other viral or bacterial infections and confirm that the proposed model did indeed pick up these patterns for prediction, and not some other features in the image, such as image label, part of CT machine, or some other anatomical part,” she says.
Parekh wants to extend this work to predict the severity of the disease, emphasising that this would help physicians in triaging and monitoring patient’s condition. She strongly believes that AI tools cannot replace radiologists, but can support them in making accurate decisions and minimising human errors. Expanding on her research, Parekh’s team has started working on another set of radiograph images — mammograms — for detecting breast cancer.
Support system
“Without my husband’s support, I would have left my job,” Parekh reflects, acknowledging the essential role her family played in her career at IIIT-H. She recalls the Saturdays spent at work early on, missing out on time with her daughter who quickly grew independent. By class 4, she was comfortable staying home alone.
Her mother’s unwavering support was another pillar, from helping her through a bedridden stretch with malaria while writing PhD thesis to caring for her daughter in those early years. This strong family foundation enabled Parekh to continue work without breaks.
On her part, Parekh makes a point to support students facing challenges with the academic system. When a woman in her 30s decided to opt out of PhD due to family obligations and evaluation issues, Parekh reached out, encouraging her to reconsider and return to her studies. “She will be graduating soon,” Parekh adds.
Her present mission is to revive the IIIT-H’s MTech Bioinformatics course, which was discontinued in 2021, by incorporating components of data science. This new curriculum will feature domain-specific and technical courses spanning two years, designed to equip students with a dual focus in both fields.
Parekh’s career story is one of transitions and deepening expertise across the natural sciences. She is the only woman among the 11 faculty members working in the Department of Computational Natural Sciences at IIIT-H. And, this has been the case for the last 20 years. “My daughter’s school had arranged an interactive session between students and women having different career paths. Such activities can really help bring about a change.”
To address the gender gap, there is a separate spec-entry for women candidates for all BTech courses at IIIT-H. “At Master’s level, we cannot do much if there are not enough women graduates. At the institute level, scholarships could be provided to girl students. Visiting colleges/institutes to create awareness about our programmes may also help,” she says.
At the same time, Parekh informs that every batch of MTech Bioinformatics has had a good number of girls, around 50% or more.
About the author
Disha Tandon is a biologist and her research career has spanned working in multiple fields in life sciences – computational biology, microbiome, and biodiversity knowledge management. Besides research, she is passionate about communicating scientific concepts – breaking down complex research published in peer-reviewed journals into digestible chunks of information. She has written for micro-bites.org and FEMS-microblogs, about the latest microbiology research and experimental biology.
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