MATE 8990 - Topics in Applied Mathematics: Algorithms for Molecular Biology

Course Announcement

MATE 8990 - Topics in Applied Mathematics: Algorithms for Molecular Biology

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.

Number of hours/credits:

3 hours per week, 3 credits


CCOM 3034 - Data Structures

Course objectives:

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.

Course schedule:

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 TopicReading
1 Introduction: History of BioinformaticsChapter 1, 2
1 Ethical Issues in Bioinformatics
2 Sequences: Nucleic Acids and ProteinsChapter 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 AssemblyChapter 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

Instructional strategies:

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

Troglodita approved!

Humberto Ortiz Zuazaga

Most recent change: 2012/1/26 at 12:15
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