Dr. Sandeep Kumar Dhanda is a Translational Bioinformatics Research Scientist at the St Jude Children’s Research Hospital, U.S.A. He has completed his Ph.D. in Bioinformatics. He has been very kindly agreed to share some insights into the field and answer some crucial questions that every newbie has in their minds.
What challenges did you face while getting into bioinformatics and how did you overcome those challenges?
The major two problems that I faced were to learn bioinformatics and to design a project in bioinformatics that would make sense. There were some challenges as I was not aware of all the computational stuff. My labmates were well trained in Bioinformatics and helped me to learn it. I was not aware initially of how to create a project in Bioinformatics. Fortunately, it was a Bioinformatics lab so designing a project was not a problem as many people were also working on similar projects
How did you get into bioinformatics?
I was doing wet lab and was not very good at it. I was doing my Ph.D. from one institute and then I moved to a different institute and in the second institute I got admission to a Bioinformatics lab but that lab was also starting its diversification in the wet lab. So I was hired for the wet lab initiative in that lab but then I realized that I was not doing it very well so I decided to switch to Bioinformatics.
What advice would you like to give to students or researchers who are willing to learn Bioinformatics, but do not have a technical background?
I don’t think learning the technical stuff is such a big problem because now we have everything available over the internet. And first, you must know what you want to learn. When you have figured out that what you want to learn then there is a well-defined path to learn. Let’s say you want to learn programming, then you have to choose which programming language you want to start with. And if you start with one like Python. Once you acquire knowledge in Python, then you can easily switch to other languages. Maybe any other language could be C or C++, Java, or any other language for that matter. So my advice is to try to find out where you want to reach, and then figure out how many ways are there to reach the destination. So the technical part is not a big of a hassle, because everything is there online, you can find many YouTube tutorials about it. Like these are the steps that you can do to learn to program, or these are steps that you could do to address phylogenetics, or vaccine design, or whatever your goal is, whatever your project is, you will find a way to address through online tutorials or online tools. Or you can also reach out to the people who are already doing this stuff. Let’s say some people are involved in research related to personalized medicine. So you can just reach out to them and say you guys are doing this stuff, how can I do it and how can I learn it, and they will be guiding you through some set of protocols they might be using. And you can just read and learn about it.
What is translational bioinformatics?
I’m glad that you asked this question. And here, I want to call to one of the things that I’m doing here in St. Jude Hospital. So what we are doing here is translating the ideas from the bioinformatics to the clinical. I’m working with the clinicians. They are seeing the patients on a regular basis and whenever they see the patient, we have a system where the patient is consented for sequencing their DNA. Once we have the molecular information or the DNA information, we try to find out mutations. Based upon the mutation that these patients are having, we are trying to relate patients with some sort of mutation or molecular profile are doing better on the treatment and the patients with a different pattern of the mutation are not doing that very well. So we should consider something that could help the patients who are not doing any good with the current treatments. So how we can find out this set of the patients is the one part of bioinformatics. The second part is how we can design therapies only targeted to those patients. Initially, the idea was one drug fits to all but now it’s changing more often in personalized medicine. And when it comes to personalized medicine, we should understand there are underlying molecular patterns that are going to be different for each patient. So we should have an idea of how we can determine those patterns and if we know those patterns then how we are going to target only those selected patterns. So there’s a part of translational bioinformatics that I am experiencing but there is way more than that I could even do or I could even explore. The other part could be, let’s say, based upon the microbiome research. Based upon a certain set of the microbiome in people, one could identify the healthy microbiome, and those coming from certain diseases. So how can we explore this healthy microbiome, taking out some bacteria from there and then inject it into the one who is suffering from a certain disease. Taking one bacteria from there and growing it into the patient might help them to recover better. That is another angle of translational bioinformatics. There is even more than that we are seeing right now, let’s say in terms of vaccine design, or in terms of medicine.So in terms of vaccines that there is a great example, for the Coronavirus vaccine, most of these vaccines have underlying bioinformatics parts, which helped to design this vaccine very quickly. You’ll be very surprised to know that the vaccine that Pfizer got approval for or the Moderna got approval for was designed in less than a week. And in this week, the scientists were computationally trying to find out which mutations or which kind of combination is going to create a stable molecule or a more immunogenic molecule. Such ideas are a part of translational bioinformatics. So I just explained three of them: the microbiome, the selecting the target or stratifying the patients, and the third is the vaccine design. These are the ones that I’m aware of, but there is way more than I could even explain.
There are many fields in bioinformatics like functional genomics, computer-aided drug discovery, protein modeling, and many more, so for a beginner will it be more beneficial to explore more domains or to create a niche in a particular field and how to choose which field to learn about?
Most people are choosing it based on the lab or the capacity they are working in and I would like to suggest they switch into something of their interest. Reading papers will help in finding the interest. Every angle of your research carries certain values, just find out the right lab to do it. It should be an overlapping of your research interest and the lab you are joining.
What should be an ideal path for a student to get into bioinformatics?
Here I will take an example from my Ph.D. supervisor Dr. G.P.S. Raghava. He often says that whenever you are doing any project you should be aware of what you are pursuing. Rather than reading anything related to bioinformatics one should be more focused on what question to answer and what project to work on. Depending on interest one can choose a project and try to figure out how to pursue it.So you should read only those things on which you will act rather than read and forget.The idea is to know where you want to reach and then exploring the path to reach that particular goal.
What is the scope of bioinformatics in India?
India has a very fertile ground for bioinformatics as we have a very good background in IT and mathematics and we could achieve similar levels in biology as well. And our pathway to enter into the biology field should be through bioinformatics. There are also advantages to getting into bioinformatics because it does not demand much investment in terms of resources. By setting up resources at a single lab, it could be shared between different labs and institutes. So, once we have got a centralized repository or centralized resources, then all the institutes could take advantage of that kind of a common resource. In that case, India is in really good shape, because we have a very good pool of experts in IT, so they can help us to set up this kind of resource environment. And we have a great pool of experts in mathematics and stats. So these two people could be connected and they could be asked to address the questions of biology. So that could be a good way to enter into the biology field and bioinformatics is providing a way to enter into there.
What should a student prefer considering higher studies in bioinformatics in India or apply abroad?
I don’t think it should be preferred based upon the location it should be depending on whom you are going to work with.In the sciences, it is fundamental to think of a question, who could help you in answering that question. So it is more often that a lab or a PI, whom you’re going to work with, is going to contribute more than the location of the lab. Some labs in India are doing way better than many labs in the US or Europe. So in that perspective, I would prefer to go to a lab of your interest or to a lab where you can grow, rather than choosing a location.
Is there any message that you want to convey to students or researchers?
I understand that bioinformatics is a growing field. And the more we know about the data the more we could make valuable things out of it. So I would recommend even if you’re not a core bioinformatician, and you are doing some wet lab stuff, still you can explore the ideas around bioinformatics and it is going to help you in your project.