Humberto Ortiz Zuazaga will be teaching an graduate course in bioinformatics Spring 2012 in UPR-RRP. Topics covered will include biological sequences, assembly, sequence alignments, sequence phylogeny, sequence database searches, whole genome analysis including transcriptome and microarray analysis, gene clustering, and application of statistics to gene profiling data.
We will emphasize the fundamental theory behind the analysis, and also present practical problems and their solutions. The course will use open-source bioinformatics tools, and show how to construct such tools using biopython, a set of libraries for bioinformatics in the python programming language.
The course is designed for graduate and advanced undergraduate students in computer science. A basic knowlege of biology is assumed. Students from other disciplines are invited to participate, but will have to make up the background.
3 hours per week, 3 credits
CCOM 3034 - Data Structures
Introduce students to fundamental concepts in bioinformatics, programming, algorithm design and analysis. After completing the course, students should be able to select tools and programs to solve bioinformatic problems and participate in their development.
Class will meet Monday and Wednesday, 3:30 - 4:50 PM in UPR-RRP, Computer Science Department, room A-141.
The proposed schedule of lectures, subject to change:
| Lectures | Topic | Reading |
|---|---|---|
| 1 | Introduction: History of Bioinformatics | Chapter 1, 2 |
| 1 | Ethical Issues in Bioinformatics | |
| 2 | Sequences: Nucleic Acids and Proteins | Chapter 3 |
| 2 | Computer platforms used in sequence analysis | |
| 2 | Brute force - Restriction mapping | Chapter 4 |
| 2 | Greedy algorithms - Gene order | Chapter 5 |
| 3 | Dynamic Programming - Pairwise Sequence Alignment | Chapter 6 |
| 1 | First Partial Exam | |
| 4 | Graph Algoritms - Sequence Assembly | Chapter 8 |
| 2 | Combinatorial Pattern Matching - Fasta and BLAST | Chapter 9 |
| 3 | Clustering and Trees- Phylogeny | Chapter 10 |
| 1 | Functional Genomics: Microarrays | |
| 3 | Statistical Methods for Analysis of Microarray Data | |
| 3 | Defining Gene Regulatory Networks: Reverse Engineering | |
| 1 | Second Partial Exam |
The professor will discuss each topic, students will complete a practical excercise for each bioinformatic technique discussed in class.
Students will be scored on two partial exams and 10 assigned works. Participation in class will account for an additional grade.
An Introduction to Bioinformatics Algorithms Neil C. Jones and Pavel A. Pevzner ISBN-10: 0-262-10106-8 ISBN-13: 978-0-262-10106-6
Most recent change: 2012/1/26 at 12:15
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