Computational biology meeting

About a new program intended to bring computational science and plant biology together. The idea is wonderful, but there's a lot of things that need to improved.

It's interesting how they start out being far away from perfect. One of the introductory computational course for plant biologists is too hard; my classmates who are taking it spent 10 hours every week to do pre-claas assignments and homework. Why so long? Because they are coding physics equations! Physics is tough as it is, and how can you learn coding with such a difficult subject?? More than half the faculty at CMSE are physicists, probably that's why. Why didn't anyone look and say "This is not an introductory level and loaded with too much physics." when they were planning courses to offer? 

Poor my classmates, they spent so much time and energy only to drop this at this point where more than half the semester is done. The help that they got from one of the TAs was "This valuable D5 can be expressed with D11, which becomes D13." What the??? It was the last straw for him. 

There's certainly so much gap to fill between computational science and plant sciences. The last time the computational students studied biology was high school. The biologists did not really study computational sciences.  They are just two entirely different things even though the collaboration of the two will offer solutions to various biological problems.

Back to the introductory course, it may be a good idea to teach what the current computers can do, what machine learning is, and what kind of problems can be addressed by using it rather than how. Similarly, what kind of biological questions are important and how raw data are generated can be taught in an introductory plant biology course. That way we will be able to familiarise ourselves with the other field, and it may be easier for us to come up with a solution to a certain problem. 

However, the interesting landscape is that computational scientists are going to provide models and help plant people with data analyses, and the opposite doesn't happen. That's what tool development and applied sciences are like, I think.

Those who don't know how hard it is to generate raw data from field work, lab experiments, and meeting people etc.. just work with computers and publicly available data from websites. What a different way of life!! I may be suited that way..