Spring 2008 STAT C141: Statistics for Bioinformatics (TT 0930-1100 285 CORY)

http://www.stat.berkeley.edu/users/hhuang/STATC141-2008.html

Lecture Notes and Home Assignments

SYLLABUS

 

Instructor:

Haiyan Huang, 317 Evans,

(510)-642-6433

hhuang@stat.berkeley.edu

Office Hours:

Tu 11-12, 2:30-3:30, or by appointment

GSI:

Megan Goldman, 315 Evans

mgoldman@stat.berkeley.edu

Office Hours:

M: 10-11, Th: 3-4

 

This course aims to introduce fundamental probability and statistics involved in Bioinformatics research and their applications to bioinformatics problems such as genome sequencing, sequence alignments, biomolecular sequence database searching, gene expression data analysis, DNA motif finding, molecular evolution models, etc. 


The homework will be assigned every other week.  In addition, there will be 3-4 short computer lab assignments. All the HWs and Labs will be due on Wednesday at the end of the lab session.  Late submissions will not be accepted without proper reasons.

There will be two in-class midterms. The first midterm is scheduled for Thursday March 6. The second midterm is scheduled for Thursday May 1st.  You are allowed to bring one page, single sided “cheat sheet” to the exam. There are no make-up tests.  Final presentations (in team) are scheduled at the end of the semester.  There will also be guest lectures (on frontier research on bioinformatics) arranged during the semester. 

Note that the above exam schedule is subject to change.

Evaluation: Students’ final grade will be determined according to the following table

20%

Homework

15%

Lab assignments

20%

Midterm I

30%

Midterm II

15%

Final Presentations

 

There is no textbook for this course. Most course materials will be posted on the class website.  The materials will be taught on a per-topic basis. 

 

Here is a list of books for major reference.

  1. Probability. Pitman J. Published by Springer
  2. Statistics (3rd ed.). Freedman, Pisani and Purves. Published by Norton
  3. Statistical Methods in Bioinformatics. Ewens and Grant. Published by Springer
  4. Computational Genome Analysis: An Introduction. Deonier RC, Tavar´e S & Waterman MS. Published by Springer Verlag, New York. 540pp. ISBN: 0-387-98785-1

Other useful books.

  1. Stat Labs. Mathematical Statistics through Applications. Nolan and Speed. Published by Springer
  2. Introduction to Computational Biology. Waterman. Published by Chapman & Hall--CRC Press.
  3. Biological Sequence analysis: Probabilistic Models of Proteins and Nucleic Acids. Durbin, Eddy, Krogh, and Mitchison. Published by Cambridge University Press