CMSC423: Bioinformatic Algorithms, Databases, and Tools (Fall 2008)

Essential details

Time: Tuesday & Thursday, 11:00am-12:15pm
Location: CSIC 1122
Instructor: Mihai Pop  (mpop at umiacs)  x5-7245
Office hours: Thursdays 1-2pm
Office address: AVW 3223

Alternate office (by appointment): 3120F Biomolecular Sciences Building (bldg #296).  
Building is usually locked.  Call me from the intercom and I'll buzz you in.

TA: MohammadReza Ghodsi  (ghodsi at cs)
TA office hours: Mondays,Wendesdays 1-2pm
TA office:  AVW 1112

Detailed Syllabus 

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Description

Computers have revolutionized modern biological research, by providing biologists with the means to manage and analyze the large amounts of data generated through high-throughput experiments.  This course provides a practical introduction to the main algorithms, databases, and tools used in bioinformatics, at the same time providing insight into the biological problems being addressed. The course will cover public databases such as Genbank and PDB, software tools such as BLAST, and their underlying theory and algorithms.  Students will learn to perform a number of useful tasks in analyzing sequence data and managing bioinformatic databases, with a focus on problems of current relevance in biological research.

You will also learn new algorithms that can apply to other areas of computer science, not just bioinformatics: clustering, string matching, basic machine learning, etc.

This course is designed to complement BSCI 348S, Comparative Bioinformatics.

Prerequisites

CMSC 351 or permission of instructor.  Programming expertise is a must.  No background in biology is required.  If you are uncertain about meeting these requirements please contact me.

Textbooks

Computational Genome Analysis

Computational Genome Analysis

An Introduction
Deonier, Richard C., Tavaré, Simon, Waterman, Michael S.
1st ed. 2005. Corr. 3rd printing, 2007, XX, 535 p. 117 illus., 15 in color., Hardcover
ISBN: 978-0-387-98785-9

Course topics

The course will cover the following main areas.  A detailed syllabus is provided here
  • Introduction to molecular biology
  • Bioinformatic databases
  • Sequence alignment: exact and inexact string matching, multiple sequence alignments
  • Phylogenetic tree construction
  • Gene prediction and annotation, microarrays and gene expression
  • Protein and RNA structure prediction, proteomics.

Coursework and grading

Regular homework assignments will consist of a combination of one or more of the following: (i) exercises from the textbook; (ii) small programming assignments; (iii) "discovery" exercises using publicly available bioinformatics tools.  In addition, all students must complete two programming projects, the first selected by the instructor and the second chosen by the students in consultation with the instructor. 

The final grades will be a combination of the grades for the homework, project, midterms and final exams.  In addition, participation in the class will be taken into account for extra credit.  The breakdown of you final grade is shown below.

Homework -  10 %
Project 1 - 15 %
Project 2 - 15 %
Midterms - 25% (12.5% each)
Final  - 35%

Unless otherwise indicated in class, most assignments will be given out on Wednesdays of each week and will be expected in by the beginning of the Monday class.  Remember, the office hours are on Tuesdays so come by if you have any questions about your assignments.

Assignments submitted late will be graded as follows: up to 1 day late - 10 points will be deducted from the grade, up to 2 days late - 20 points  will be deducted.  Your assignment will not be graded beyond the second day past the deadline.  If for reasons outside your control you will not be able to submit an assignment on time, see me as soon as possible to discuss an alternate deadline.

Attendance policy

This course follows the University's attendance policy.  In short, if you will miss class for any reason you should let me know in advance,  unless this is not possible (e.g. sudden illness).  In any case, please let me know as soon as you are aware that will not be able to attend a class (e-mail is OK).  I will work with you to help you catch up on homework or exams if you have to miss any of the lectures.  

Academic integrity

I expect that the students taking this class fully adhere to the Code of Academic Integrity.  Please read this document in full if you have not already done so.  In addition, the University requires that you sign the Honor Pledge on every examination you turn in.  Please read the relevant excerpt from the Code of Academic Integrity (reproduced below).