Integrating Biology And Algorithms To Analyse Data: Punit Kaur

Meha Mathur Sep 14, 2022

One of the promising fields in biosciences is bioinformatics, involving the understanding of both biology and computer science. To understand its present-day relevance and scope, BW Education spoke to subject expert Punit Kaur, Head of Department, Dept of Biophysics at AIIMS. Excerpts from an exclusive interview:

What is bioinformatics as a field all about?

Bioinformatics is the integration of biology with computer science or algorithms to manage and interpret the massive and complex biological data available. Some decades ago, information was very limited, but now, with the exponential data deluge, there is a need to accumulate the data, put it in one place and ensure uniformity across data of similar kinds. There are two aspects: generating the data and collating it. All biological data needs the support of a data scientist or bioinformatician to interpret the data and derive a meaningful conclusion.

And what are the applications?

There are several areas of biology where bioinformatics can be applied. One example is the interpretation of next-generation sequencing of genomic data – eg sequencing the whole genome of an organism and its comparison from similar sequences across the world. So, suppose, I do the sequencing of a genome of one organism in Delhi and another researcher does it from a similar organism in Chennai and Hyderabad and in any other part of the world. This sequencing data can be collated together by creating a database, where we can input and store our respective data onto that computational platform. Here, the front end is where you have an interface to feed the data and the back end is where all the technology comes in. Bioinformaticians can access and mine the data collated in this database through the internet/web from their respective locations with the help of computational tools and can arrive at a meaningful conclusion based on the combined or individual data.

Another aspect is molecular modelling, structural bioinformatics and drug discovery. Here the initial information comes from an available protein structure, eg haemoglobin. The three-dimensional structures of proteins are available in the protein data bank. Hence, if I want to model the structure of a protein, I search the protein data bank, for a similar structure. Now to find out the similarity between two structures – you compare the amino acid sequence of the proteins of interest ie sequence alignment.

So, here again, bioinformatics comes into play. Finding out information about closely related sequences, and their structures, subsequent structure prediction followed by drug design and discovery form different aspects of bioinformatics.

Earlier, to understand the processes of ‘absorption, distribution, metabolism and excretion’, for efficacy and safety issues of drugs in the drug discovery pipeline, animal trials were conducted. Now, with animal trials becoming complicated, we can use computational models instead of actually conducting these experiments. This is where bioinformatics again comes in — deriving meaningful information from the biological data that you have and developing and using computational tools to determine ADME. Thus, what would have earlier taken five or six years, can now be achieved in a shorter time. We still have to conduct the clinical trials. But the overall time, from actually finding the drug candidate to treat a disease, to clinical trials and marketing the drug gets significantly reduced.

Some other aspects of bioinformatics besides storage and retrieval of data in biological databases, drug discovery and genomics include gene therapy and genome applications, image data interpretation and analysis, molecular medicine and precision medicine.

What kind of aptitude is required for this field, especially for youngsters who want to join?

You should not enter a field without being fully aware of it. Bioinformatics requires extensive interpretation of biological data. Hence, it is not just about knowing and understanding biology; basic knowledge about programming languages is also required. As a biology student, you should be ready to learn a bit about computer programming. And if you are a computer scientist, then you must have an understanding of biology. Presently, it is all about collaboration with other researchers with complementary skill sets. Still, you should take an active interest and be aware of the other aspects of the field.

Is there enough infrastructure for studies in India, and also, what is the scope of the subject here?

There is very good infrastructure, with DBT, DST and ICMR having dedicated institutes. We have C-DAC (Centre for Development of Advanced Computing) with high-end super computational facilities accessible across India. DBT has established several Biotechnology Information System Networks (BTISNet) wherein excellent work is being conducted related to bioinformatics.

There is tremendous scope. However, people with in-depth knowledge are required. Opportunities exist in the field of drug discovery, genomics, proteomics, data science in pharmaceutical and data science companies and hospitals. There are several companies in bioinformatics in India together with a number of startups, especially relating to the analysis of next-generation sequencing data. Moreover, you do not require huge investments for startups where the main core strength is data analytics.

What would you say about STEM education in schools, and are schools now preparing students adequately for such studies at higher levels?

Yes, in school, under STEM education all basics are taught in biology, as well as in computer sciences. You can add to that knowledge by learning an additional programming language. There is no dearth of courses on the internet now. In fact, it’s a good idea to pursue practical courses as sometimes, just a basic degree in biology or bioinformatics may not be adequate from the job perspective in the industry.