Skills to study computational biology?

In summary, you will need a good level of differential equations and stochastic processes, as well as information theory and some knowledge of learning theory to study computational molecular biology. Additionally, you will need to focus on learning the mathematical concepts behind systems biology papers that are of interest to you.
  • #1
kostismed
1
0
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
 
Biology news on Phys.org
  • #2
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.
 
  • #3
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/bioinformatics/modules/index.html [Broken]
 
Last edited by a moderator:
  • #4
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)
 
  • #5
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.
 
  • #6
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 - https://www.physicsforums.com/showthread.php?t=574876&highlight=Hysteresis+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/
 
Last edited:

What is computational biology?

Computational biology is an interdisciplinary field that combines biology, computer science, and mathematics to analyze and interpret biological data. It involves using computational tools and algorithms to study biological systems and processes.

What are the skills required to study computational biology?

The skills required to study computational biology include a strong foundation in biology, computer programming, statistics, and data analysis. Additionally, critical thinking, problem-solving, and communication skills are essential for success in this field.

What programming languages are commonly used in computational biology?

Some commonly used programming languages in computational biology include R, Python, Java, and C++. Each language has its strengths and is used for different purposes, such as data analysis, modeling, and simulations.

Do I need a background in biology to study computational biology?

While a background in biology is helpful, it is not always necessary to study computational biology. Many computational biologists come from diverse backgrounds such as computer science, mathematics, or physics. However, a basic understanding of biology is important to interpret and analyze biological data accurately.

What career opportunities are available in computational biology?

There are various career opportunities in computational biology, including bioinformatics analyst, data scientist, computational biologist, and research scientist. These roles can be found in academia, government agencies, pharmaceutical companies, and biotechnology firms.

Similar threads

Replies
4
Views
668
  • STEM Academic Advising
Replies
2
Views
1K
  • STEM Academic Advising
Replies
17
Views
3K
  • STEM Academic Advising
Replies
7
Views
1K
Replies
3
Views
259
  • STEM Academic Advising
Replies
9
Views
1K
  • STEM Academic Advising
Replies
2
Views
734
  • STEM Academic Advising
Replies
2
Views
1K
Replies
3
Views
139
Replies
4
Views
786
Back
Top