Computer Science 245/345
Introduction to Bioinformatics
Summer 2016: June 6 to June 24
Monday, Tuesday, Wednesday, Thursday, Friday: 10:00 to 1:00 pm
Helpful links
Remark
Biology is not a prerequisite for this course. But an interest in Biology is.
I will spend the first 2 lectures of the course
going over some notions in biology. See
Biology Terms.
Information about the Instructor
Name: Sami Khuri, visiting professor from San Jose State University
Office: 335W
Phone: TBD
Office Hours: TBD
Email: sami.khuri@sjsu.edu
Catalog Description
The course starts with a brief introduction to molecular biology. The
course then investigates the main algorithms used in Bioinformatics. After
a brief description of commonly used tools, algorithms, and databases in
Bioinformatics, the course describes specific tasks that can be completed
using combinations of the tools and Databases. The course then focuses on
the algorithms behind the most successful tools, such as the local and
global sequence alignment packages: BLAST, Smith-Waterman and Needleman-
Wunsch.
Lecture topics include Hidden Markov
Models for pattern recognition, conducting profile-based searches,
phylogenetic tree
construction, and transmembrane protein structure prediction;
The course is self contained
and does not assume any background knowledge in biology,
although an interest is molecular biology is helpful.
The course will also be complemented
by hands-on, computer lab sessions that will allow students
to practice with some of the major tools and databases.
Students will solve hands-on problems on HIV, BRCA1 gene, Thalassemia,
MYH, etc...
Students will be given projects that will have to be completed and
submitted by midnight (California time) on July 29, 2016.
Purpose
To acquaint students with some of the most challenging problems in life
science and show how computer science can be used to better
understand and in some cases, solve some of these
problems.
Objectives
- Show how elementary techniques are used in bioinformatics:
- Pairwise alignment (local, global, semiglobal)
- Homology and similarity
- Multiple sequence alignment
- Database searches
- Phylogenetic tree construction
- Show how Hidden Markov Models can be used for gene prediction and
for protein profile construction
- Study various folding algorithms to predict RNA secondary
structure
- Study various probablilistic techniques for identifying genes,
promoters, etc..
- Perform hands-on exercises on genes and genomes such as HIV,
BRCA1, Thalassemia.
Learning Outcome
Upon successful completion of this course, students should be able to use
dynamic programming for pairwise alignment and (to some extend) for RNA
secondary
structure prediction (Nussinov's algorithm), to understand how multiple
sequence alginment algorithms work, to have a clear understanding of
phylogenetic tree algorithms, and to know various databases for DNA and
protein sequences. They should be able to assess and evaluate novel
computational methods for use in bioinformatics, including machine
learning techniques, mainly Hidden Markov Models, and pattern recognition
techniques.
Lecture Material and Schedule
Recommended Textbooks (Not required)
-
Understanding Bioinformatics
by Marketa Zvelebil and Jeremy Baum,
Garland Science, 2008, ISBN 0-815-34024-9.
-
Introduction to Computational Molecular Biology by J. C. Setubal and
J. Meidanis.
PWS Publishing Company, Boston, 1997.
-
Bioinformatics and Functional Genomics
by Jonathan Pevsner, John Wiley, 2003.
- We shall cover most of the topics from:
- chapters 4 to 12 from Zvelebil and Baum,
- chapters 1, 2, 3, 6 and 8 from Setubal and Meidanis, and
- chapters 1 to 4, 10, 11 and 17 from Pevsner's textbook.
- Additional topics will be covered.
- A copy of my notes (6 slides per page) will be available for
download.
Copies of lecture notes, hands-on exercises and case studies for all
classes, from Monday, June 6, to Friday, June 24, 2016, can be found
here.
Cover Sheet
Course Requirements
Term Project
There will be a group
project.
Each group consists of two students.
The group chooses a topic
and writes a term-project. The group will choose only one topic from the
five suggested topics. Alternatively, the group suggests their own project
by submitting a one-page proposal describing their project, by noon on
Friday,
June 16. If accepted, the group needs to submit their work by the
deadline.
The term-project is due by 11:59 pm PST on Friday, July 29, 2016.
The cover sheet for the project (pdf).
The cover sheet for the project (doc).
Exam:
Final Exam:
In-class, closed-book and comprehensive. Date: Friday, June 24, 2016.
Review sheet for Final Exam.
Grading Policy
The final grade will be computed as shown below:
Hands-On Exercises 30%
Term-project 30%
Final Exam 40%
Note: Students get full credit on Hands-On Exercsies as long as they are
in class during the discussion of the solutions of the problems. Students
marked absent will have to hand in a hard
copy of detailed solutions of the hands-on exercises they missed (if they
want to get credit for the exercises that were solved and discussed during
their absence). The submission will have to be done within 2 days of the
absence. It is not meant to be as a punishment, but rather to make sure
that students do not fall behind.
[97, 100] A+
[93, 97) A
[90, 93) A-
[87, 90) B+
[82, 87) B
[80, 82) B-
[77, 80) C+
[72, 77) C
[70, 72) C-
[67, 70) D+
[62, 67) D
[60, 62) D-
[0, 60) F