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-   -   Skills to study computational biology? (http://www.physicsforums.com/showthread.php?t=230531)

kostismed Apr22-08 06:08 AM

Skills to study computational biology?
 
Hi. I just finished medical school and I want to start studying computational biology (and maybe pursue a PhD at systems biology). I have a very good level of physiology knowledge but, as most medical students, I am not good at mathematics. So every time I start reading a book, I mess it up when it comes to the mathematics section (which I feel is the basis of computational biology). Have you any idea what mathematical skills and knowledge I need to study computational biology? Thanks

Cincinnatus Apr23-08 01:00 AM

What area of biology are you interested in?

In computational molecular biology the primary tool is biophysical modeling. A good knowledge of differential equations and stochastic processes should be enough to get started reading the literature in the field.

For computational neuroscience you will also need to understand information theory and have some amount of learning theory to understand a large part of the literature.

redheather May17-11 12:52 PM

Re: Skills to study computational biology?
 
At the University of Manchester we teach a range of distance courses in computational biology. The courses are designed for people with a background in the life sciences or in computer science, and we have quite a few students with a medical background. We aim to teach through problem solving, so each of the courses is based around practical problems.

One of our most popular courses has been 'Theory and Applications in Bioinformatics', using Matlab. We used a lot of graphics to explain the methods, and students then designed their own applications in Matlab.

As we now have a new theme in systems biology, we have a new course in 'Mathematics for metabolic modelling'. For this course we are using R, another language for mathematical programming. Again, I think that the graphics in R help people to understand the mathematical concepts.

You can see a list of all our courses here : http://octette.cs.man.ac.uk/bioinfor...les/index.html

Pythagorean May17-11 02:00 PM

Re: Skills to study computational biology?
 
I agree with what's been said here:

stochastic methods (i.e. markov models)
differential equations (and the prerequisite calculus)
matlab programming (or some other common language)
information theory

and will add:

nonlinear dynamics and chaos theory (Strogatz is a good author)

Fantasmagoria Mar8-12 11:47 PM

Re: Skills to study computational biology?
 
I would also recommend finding papers in systems biology that are interesting or relevant to you, and focusing on learning the mathematical concepts behind those.

epenguin Mar10-12 12:52 PM

Re: Skills to study computational biology?
 
People could more helpfully advise if they knew what country you are or will be in.

However when I was last in contact with it (ten years ago :frown:) your chosen general field had good employment outlets as the interdisciplinarity and modelling skills and experience is useful to employers in industry and in government or government-sponsored research (e.g. epidemiology, environmental management etc.). There seems no reason that should have changed. Physiology is a good starting point.

We will probably fling more book titles at you than you can read. However I recommend

Modeling Dynamic Phenomena in Molecular and Cellular Biology by L. Segel (an early edition will be OK.) This is specifically written for biologists and contains possibly the biologist-friendliest presentation of basics of how to deal with the typical nonlinear differential equations, indispensable and met all the time. Have been discussed on this site e.g. recently - http://www.physicsforums.com/showthr...+steady+states


For a field adjacent in the other direction you might look at
Physiological Ecology of Animals :
An Evolutionary Approach
by R. M. Sibly, Peter Calow

A look at this guy's publications suggests a vastness of applicative areas.

http://www.bookfinder.com/author/peter-calow/


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