BME 537/CSE 587A

Computational Molecular Biology, aka
Algorithms for Computational Biology

Fall 2015

News and announcements

  • Unsure where to go: check the directions.
  • A copy of the deGroot book, Probability and Statistics, is on reserve at the Becker (medical campus) library.

Subjects This course is a survey of algorithms and mathematical methods in biological sequence analysis (with a strong emphasis on probabilistic methods) and systems biology. Sequence analysis topics include introduction to probability, hidden Markov models, gene prediction, sequence alignment, and identification of transcription-factor binding sites. Systems biology topics include discovery of gene regulatory networks, quantitative modeling of gene regulatory networks, synthetic biology, and quantitative modeling of metabolism.

Approach Our teaching philosophy is shifting from lecture-based to active learning. This means you will be expected to learn the basic material outside of class, through reading and working problems. In class we will emphasize discussion and working on problems and projects. Passive observers never learn much, but in this environment it will be more obvious. If you are registered for the course, active participation in class is an absolute requirement.

Prerequisites To take this course you must have taken

·      A course in computer programming (or equivalent experience)

·      A course covering basic molecular biology equivalent to a high-school Advanced Placement course or an introductory college course

·      A course covering basic differential and integral calculus (high school or college level)