CSE 549 - Introduction to Computational Biology

Course Notes

• The permanent site for 549 videos is http://www.algorithm.cs.sunysb.edu/computationalbiology/. Check them out!
• See this excellent writeup on Hidden Markov Models
• Watch the excellent videos on transcription and translation of DNA.
• To study for the midterm I recommend you look at an old example midterm and the problems on the old Homeworks 1 and 2 given below.
• I encourage students to take advantage of the CSHL's SBU-friendly meeting policy to attend conferences/meetings at Cold Spring Harbor Laboratory.
• Olivia Judson writes a terrific blog on evolutionary biology at the New York Times, which I strongly recommend to all. Particularly relevant for our class is The Fantasy Genome Project.
• This ridiculous, CS-centric view of DNA might be helpful to some.

Course Documents

• Course syllabus
• Lecture Schedule
• Course project list (now with Fall 2011 projects!)

Homework Assignments

• Homework 1: Assembly and Data Bases

  The answer key is now available. The breakdown by problem is 1: 10pts 2: 10pts 3: 30pts 4: 15pts 5: 10pts 6: a) 5, b) 5, c) 15. The total was 100 points.

• Homework 2: Sequence Comparison and Gene Prediction . Source code for a C language dynamic programming program for edit distance computation is is available here.

  The answer key is now available. The breakdown is 10pts per problem, for a total of 60 points.

  General Resources

  • The Bioinformatics Education Resource contains powerpoint presentations, practical bioinformatics problems, implementation problems, sample implementations, and problem solutions.
  • The Genetic Science Learning Center at the University of Utah has a lot of information about biotechnologies and genetic diseases.

  Books

  The textbook for this course will be:
  • Jones and Pevzner, An Introduction to Bioinformatics Algorithms MIT Press, 2004.

  The following books are recommended:

  • Gusfield, Algorithms on Strings, Trees, and Sequences : Computer Science and Computational Biology, , Cambridge University Press, 1997.
  • Durbin, Eddy, Krogh, and Mitchison, Biological Sequence Analysis : Probabilistic Models of Proteins and Nucleic Acids , Cambridge University Press, 1998.
  Additional books of possible interest are:
  • Setabal and Meidanis Introduction to Computational Biology , PWS, 1997.
  • Claverie and Notredame, Bioinfomatics for Dummies, For Dummies Press, 2003.
  • Pevzner, Computational Molecular Biology: An Algorithmic Approach, MIT Press, 2000.
  • Dwyer, Genomic Perl Cambridge Univ. Press, 2003
  • Mount, Bioinformatics: Sequence and Genome Analysis, Cold Spring Harbor Laboratory, 2001
  • Bishop and Rawlins DNA and Protein Sequence Analysis : A Practical Approach , Oxford University Press, 1997.
  • Baxevanis and Ouellette, Bioinformatics , Wiley, 1998
  • Sankoff and Kruskal, Time Warps, String Edits, and Macromolecules , CSLI Publications 1999 (reprint).
  • Watson, Gilman, Witkowski, and Zoller, Recombinant DNA , Scientific American Press, 1992.
  • Skiena, The Algorithm Design Manual Springer Verlag, 1998.

  Related courses at other Universities

  • Stanford
  • University of Washington
  • Johns Hopkins
  • UC Riverside
  • MIT
  • Tufts
  • RPI
  • Brown
  • Univ. of Texas">
  • Univ. of Bristol
  • Cornell
  • Columbia

  Join the Algorithm Reading Group (CSE 642) at Stony Brook!