Computational Biology
Learn and apply a breadth of skills to tackle intriguing problems like RNA folding and genome reconstruction.
21 LessonsOrder and Information
Course description
This course was written in collaboration with quantitative biologists and biophysicists from leading research groups at Caltech and Duke.
Computational biology merges the algorithmic thinking of the computer scientist with the problem solving approach of physics to address the problems of biology. Since the year 2000, an ocean of sequencing data has emerged that allows us to ask new questions.
Topics covered
- Algorithms (Python)
- Ancestry
- Data Analysis (Python)
- DNA Sequencing
- Forensics
- Genetics
- Genotyping
- Molecular Biology
- Mutual Information
- Nussinov Algorithm
- Protein Folding
- RNA Folding