CS 5263 & CS4233 (Bioinformatics)

News and Announcements

4/25: HW3A description. Data file. Matlab code output. Matlab code

4/13: Example test questions.

3/20: MATLAB Tutorial

2/23: Midterm project is here. Electronic submission in blackboard due on 11:59pm, March 21 (Extened to: Friday, March 24), 2017. Notes.

2/16: fixed some typos in HW2 problem 1(c) and 1(d), 4(g), and revised 2(b) and 2(d) for more accurate instructions.

2/12: HW2 due on Thursday Feb 23. Download DNA sequence file for problem 1E (optional).

1/22: HW1 due on Tuesday Feb 7. Download DNA sequence file for problem 3, text file 1 and text file 2 for problem 4. Solution

1/10: Welcome to CS4233 & CS5263 (Bioinformatics)! Please take some time to complete a background survey.

Overview | Prerequisite | Time and Location | Instructor | Textbooks and Resources | Policies | Lecture Schedule and Slides | Assignments

Overview

This course is a survey of algorithms and methods in bioinformatics and computational biology, approached from a (more or less) computational viewpoint. Topics covered include: fundamental biology, sequence comparison (dynamic programming), motif finding (combinatorial algorithms, stochastic heuristic search algorithms, suffix trees), next-generation sequencing (suffix array, Burrows Wheeler transform), gene expression data analysis (statics, data mining), and gene network/pathway analysis (graph algorithms).

Prerequisite

This course is primarily designed for graduate students and advanced undergraduate students in the Computer Science department. Fundamental understanding of data structure, algorithms, excellent programming experience in at least one programming language, as well as some knowledge of probability and statistics are expected. Some prior exposure to molecular biology is preferred, but not required, as we will introduce basic biological concepts and terms along the way. Students without background in Algorithms or Statistics should consult the instructor prior to taking the course.

Time and Location

We meet in room MH 3.02.30. Lecturers are Tuesday and Thursday, 2:30-3:45 PM.

Instructor and TA

Instructor: Dr. Jianhua Ruan
Office location: NPB 3.318
Office hours: Tuesday 9-11am or by appointment
Email: jianhua.ruan 'at' utsa 'dot' edu
Phone: (210) 458-6819

Teaching Assistant: TBD
Office location: TBD
Office hours: TBD
Email: TBD

Textbooks and Resources

There is NO textbook required for this course. Parts of the course are based on the text:

Grading Policy

Late assignments will not be accepted and a score of zero will be given, unless approved by the instructor.

Collaboration Policy

Assignments

Lecture Schedule and Slides

Part I: Introduction to bioinformatics and molecular biology

Part II: Sequence alignment

Part III: Motif finding

o    Statistics and Probability Primer for Computational Biologist

Part IV: String matching and short-read mapping

Part V: RNA secondary structure prediction

Part VI: Hidden Markov models and gene prediction

 

Part VII: Transcriptomic data analysis and data mining

 

Part VIII: Biological networks

         slides

 

Tentative lecture topics

Topics

Number of weeks

Introduction to molecular biology

1

Sequence alignment

2

String matching algorithms and applications

2

Motif finding

1

RNA structure prediction

1

Transcriptomic data analysis and data mining

4

Next-generation sequencing

2

Biological networks

1