Quaere verum

Scientists search for truth. S/he should be a stickler for truth. Report only truth, nothing but truth. It is sometime hard thing to do. Especially in modern molecular biology, which is become highly interdisciplinary. In order to completely understand new age biology one must have a fair amount of knowledge in multiple branches of science; statistics, computer science, mathematics, to name a few, in addition to the traditional training in biochemistry, genetics, biophysics and molecular biology. I am in the early phase of learning computer science. Many concepts are completely new to me. Same is the case with statistics. How can one individual have such a good grasp on these diverse topics? Historically, many biology students are considered not good with numbers.  At least for people from my generation who did most of the undergraduate education in 1990’s there was very little overlap between biology and other natural sciences. There was biochemistry, which is supposed educate one on chemical basis of life. Many students used to take statistics, but to those who are not into serious genetic analyses, the application of which was mostly limited to (mostly inappropriate use of) Student’s t-test and ANOVA.

I believe students who graduate in recent years tries to get an understanding on mathematics, statistics and programming. With the advent to cheaper personal computer, Internet and Massive Open Online Courses (MOOCs) such knowledge is becoming accessible to many oldies from my generation too. But its harder to learn subjects which required lots of time investment such as CS and statistics. In my opinion, it is not due to decreased plasticity of ageing brain, but due to lack of quality time available to invest in learning new subjects (I would love to talk to people who have successfully done these tasks, to learn their strategy). At any rate, a decent grasp on these subjects is becoming inevitable for modern molecular biologists. It is hard. But many of the data sets produced by genomics experiments require intense computational analyses. There may be people with expertise in each area (such as statistics, programming, bioinformatics…) to help with the analyses, but as person responsible for the published data based on these multidisciplinary effort, I feel obliged to study all these subject to ensure that analyses are done properly and most importantly, the result is true to the core!

I always felt that me (and my generation) fell right in between two generations; one who escaped the need for multidisciplinary knowledge and therefore did not (actively) learn it (80’s and earlier) and second who had thorough multidisciplinary education at undergrad level and therefore applied it in research (2000’s). But in my case, the education was of 80’s style, but the science demanded the knowledge level of 2000’s. Although sometime I feel it as an unfair deal, to the most part I feel happy. It will definitely keep me engaged and expose me to areas that I always wanted to learn more about. Most importantly it would allow me to explore new and exciting areas of science, to translate population and quantitative genetics data to tractable molecular biology questions.  It’s an awesome time to do biomedical research, to end it in high note!