Nowadays, scientists can use computers to produce several hypotheses as to how a particular phenomenon works, create computer models using the parameters of each hypothesis, input data, and see which hypothetical model produces an output that most closely mirrors reality.
With computational biology, researchers apply mathematics to biological phenomena, use computer programming and algorithms to artificially create or model the phenomena, and draw from statistics in order to interpret the findings. In this course, you will learn the basic principles and procedures of computational biology. You will also learn various ways in which you can apply computational biology to molecular and cellular biology, biochemistry, neuroscience, evolution, population biology, and behavior.
Upon completion of this course, students will be able to:
- Define computational biology and provide examples of how it is used.
- Describe how networks, algorithms, and models are employed in biology.
- Describe how DNA and proteins are manipulated to generate information from sequences and whole genomes.
- Describe how biological processes can be modeled using computer programming.
- Identify techniques for gathering information on proteins and their interactions.
- Provide examples of the use of mathematics in evolution and behavior.
- Describe the current applications of computational biology.