Doing PhD is indeed one lifetime experience for every PhD candidate. But what is interesting is that every PhD tale has its both unique and comparable narratives. As it is notorious for, PhD comes with lot of challenges and hurdles. Before even trying to start answering the research question that you yourself propose, you need to answer and walk through a trail of many questions. First answer them and satisfy your soul. And get convinced. The very first and foremost question is to ask if you really want to do a PhD. Are you a PhD material? Can you devote your next 5 years studying? Can you make your PhD studies both your friends and family? Most importantly, does it align with your life’s goal??? And once you examine the depth of your intent and interest in doing a PhD, then comes rolling the never ending list of deciding the school, your advisor, thesis topic, and further on.
For me, the director of computer science in an ok not a great university, owning a bioinformatics lab called me and interviewed and showed interest in me. This meant I already had my advisor when I started my PhD. When I joined his lab, I was expected to take over the project of a former graduating PhD student in our lab. I heard it is very common in biology community to first take over projects from previous PhD students in your lab and then only think what you yourself want to do. For that, I had to fully understand his whole software written in C and develop its web application for its users to be able to access and run it on web on our servers. So my first year spent in understanding that software and building its webserver. It was indeed, a very useful learning experience. I developed the online tool and wrote a conference paper as its first author.
Having understood the software so well, I started taking up services where our collaborators wanted to use that tool. And on side I was also digging its various projects that it had been used for, in past. I found one of our collaborators projects and its result sitting in our computers for last two years. The results looked so promising and representing one unique feature of that tool, unnoticed till then. I polished that feature of that tool and further analyzed those results. Eventually after prolonged efforts of bringing together all the past collaborators on that project to provide me with more details, I finally wrote a paper and got it published. It is always advised to take care of the low hanging fruit first. It was hard to get all the authors back to their 2 years old project and review a long research paper with absolutely different angle than the project they used that tool for. Reminding busy professors and struggling new post-doc for reviewing the paper I wrote was a tough job by itself for naïve, immature PhD student.
And, only after my fairly successful 2 years came my very first real challenge to decide on my thesis topic. It was not just the specific thesis topic but also to first decide the broader field of bioinformatics applications, where I wanted to focus. There are various directions where you can streamline your phD studies. One is to focus on your algorithmic and computational skills and try to develop a tool or software that everyone in your community and research can use and benefit from. The other is to go towards the consumer side where you dwell upon the available tools and use it in your favor and come up with new findings.
To me it is more useful for the community to help improve upon an existing tool based on your needs rather than reinventing the whole wheel. Having PhD record, as one of the requirements of a PhD is a feature to show your potential and caliber. However, software designed for the sake of publication in mind or develop a software with goal of adding just a single feature to outperform or compete among zillions of other tools is injustice towards driving bioinformatics forward. The number of bioinformatics web applications and tools for example sequence aligners, genome assemblers or mappers, and many other bioinformatics software’s are many folds higher than the ones that are actually used.
Also, if I wanted to focus on building algorithm, next thing to do was either look for some other collaborator of our lab for a project that needs a better algorithmic design or find one myself. But for the second direction, I had to only decide on a particular disease that I’m really interested in and practically feasible to conduct research. And for that, Cancer was the very prompt and feasible answer with lots of available online dataset and unanswered questions.
However, knowing the expectations from not only my advisor but also the department and the peers for a graduate student to only conduct one top-notch research and answer questions never heard before causing cancer, I initially desired more to only investigate fundamental questions in biology. But only after I realize its importance and applicability in understanding the underlying biological processes leading to cancer. I do believe, from such understanding leading to cancer oriented changes, new treatments can arise. And I decided to start working working specifically on cancer.