Representations and Algorithms for Computational Molecular Biology


Stanford School of Medicine



The explosion of molecular data continues to fuel academic and industry interest in biomedical informatics. This is an exciting time in bioinformatics, and there is great potential for harnessing information produced by genome sequencing projects for medical diagnostic and therapeutic uses.

This course provides an introduction to computing with DNA, RNA, proteins and small molecules. Learn how to program both basic and advanced algorithms for sequence analysis, 3D structure analysis and high-throughput functional data analysis. Receive hands-on experience with the algorithms used in the field.

Non-Degree Option students are required to enroll for 4 units.
3 unit enrollment is only allowed with instructor approval.

What you will learn

  • Computing with strings
  • Phylogenetic tree construction and hidden Markov models
  • Protein structural computations, structure prediction and threading techniques
  • Molecular dynamics and energy minimization
  • Statistical analysis of 3D biological data and integration of data sources
  • Machine learning (clustering and classification)
  • Natural language text processing


CS106B; CS161 is recommended.


Course Availability

The course schedule is displayed for planning purposes – courses can be modified, changed, or cancelled. Course availability will be considered finalized on the first day of open enrollment. For quarterly enrollment dates, please refer to our graduate education section.

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