Drug Discovery vs. Bioinformatics

Before I went to collage, I knew that I wanted to be a doctor or I wanted to study genetics engineering. I didn't do either! Instead, with my far-sighted parents' guidance, I studied computer science (technically I have a BS in computer engineering, but the science stuff was more interesting to me..). But, I used my passion for biology and genetics wisely, and took as many genetics and statistics classes as I can during my undergrad. I also told my undergrad-advisor that I would like to specialize in 'bioinformatics'. 

My undergrad-advisor was a wonderful, smart(ass) guy, who in return told me that bioinformatics is not an established area of computer science. Now we are talking about (*gasp*) ten (10) years ago! 

In the past 10 years, I didn't take his advice, and I worked on many different bioinformatics projects. I bumped into my advisor during my research year in Germany while he was trying to get involved with a bioinformatics team! The other thing that happened in the past ten years is the definition of bioinformatics. 

When I started to get involved in bioinformatics, you really didn't need to know any biology. It was almost as if biologists were realizing that there is this machine called "computer" and it can run computational stuff faster than they can hand-trace networks! 

Over the years the computers and bioinformatics both evolved. The computational powers increased; the storage and speed related problems decreased rapidly. In addition, more and more people used existing computational solutions on existing data. So people needed to know the biology, computer science, and come up with NEW solutions to the problems. 

Now I am seeing a similar development in the drug discovery! Currently, it is almost like pharma companies are saying to themselves: "Wait! There is this machine called 'computer' and it can reveal results that we might be interested in without running thousands and thousands of assays!"

This time though, we are skipping a step, and we cannot getaway with blindly applying any computer algorithm to data and claim that we have "interesting" findings! It will be interesting to see how this "commercial" need for life-science computations will change the face of different sciences.