Syllabus

course description

This is a full-lecture, graduate course on algorithms and biomedical applications. The Foundations lectures are an introduction to the biological and medical genomics application areas. Each Algorithm section is devoted to an algorithmic method presented in rigorous depth, followed by an important open problem in the application area, together with the current most effective algorithmic solutions to the problem. Graduate students and advanced undergraduates in computational and mathematical sciences and engineering are welcome. Biological, life sciences and medical students and faculty are welcome as well and will be able to participate more in the applications areas.

structure of the course

professor: Sorin Istrail TA: TBD
CIT office: 523 TBD
email: sorin -at- cs@brown.edu TBD
office hours: TBD TBD

time and place

Tuesdays and Thursdays 2:30-3:50 CIT 241 SWIG Boardroom

prerequisites

The course is designed for graduate students and upper-level undergraduates. It is open to students with a background in computer science, engineering, or computational and mathematical disciplines. This course requires CSCI0320, CSCI0330, graduate standing, or an equivalent programming intensive course and CSCI1820 or permission from the instructor. Basic knowledge of data structures and algorithms is required but prior knowledge in biology is not. Please contact the instructor if you are unclear as to whether you have the necessary prerequisites for the course.

homework

There will be four problem sets including programming and student presentations on algorithmic research articles. Programming assignments must be able to run on department machines and include a README describing how to run the algorithm.

grading

  1. homeworks 50%
  2. class participation 10%
  3. presentations 10%
  4. final project 30%

Extra credit will be given for original contributions to research projects and the most impressive submissions will be awarded a Pastiche pie prize!

readings

Each major section will have a set of recommended research articles for readings.

collaboration policy

You may discuss the homework problems with other students. However, you must not obtain answers directly from anyone else. All homeworks will be submitted individually.