Biol425 2011

Computational Molecular Biology

BIOL 425/790.49, Spring 2011

Hunter College of the City University of New York

Course information

Instructors: Che Martin and Yozen Hernandez

Class Hours: Room 1000G HN; Saturday 11am-2pm

Office Hours: Room 839 HN; Thursdays 12-2pm or by appointment

Contact information:

Che: cmartin@gc.cuny.edu, 917-684-0864
Yozen: yzhernand@gmail.com, 347-829-6936

Course Description

Background

Biomedical research is becoming a high-throughput science. As a result, information technology plays an increasingly important role in biomedical discovery. Bioinformatics is a new interdisciplinary field formed between molecular biology and computer science.

This course will introduce both bioinformatics theories and practices. Topics include: database searching, sequence alignment, molecular phylogenetics, structure prediction, and microarray analysis. The course is held in a UNIX-based instructional lab specifically configured for bioinformatics applications. Each session consists of a first-half instruction on bioinformatics theories and a second-half session of hands-on exercises.

Learning Goals

Students are expected to be able to:

Approach biological questions evolutionarily ("Tree-thinking")
Evaluate and interpret computational results statistically ("Statistical-thinking")
Formulate informatics questions quantitatively and precisely ("Abstraction")
Design efficient procedures to solve problems ("Algorithm-thinking")
Manipulate high-volume textual data using UNIX tools, Perl/BioPerl, R, and Relational Database ("Data Visualization")

Pre-requisites

This 3-credit course is designed for upper-level undergraduates and graduate students. Prior experiences in the UNIX Operating System and at least one programming language are required. Hunter pre-requisites are CSCI132 (Practical Unix and Perl Programming) and BIOL300 (Biochemistry) or BIOL302 (Molecular Genetics), or permission by the instructor.

Textbook

Krane & Raymer (2003). Fundamental Concepts of Bioinformatics. Pearson Education, Inc. (ISBN 0-8053-4633-3)

This book should be available in the Hunter Bookstore, as well as through several popular retailers and resellers online.

Grading & Academic Honesty

Hunter College regards acts of academic dishonesty (e.g., plagiarism, cheating on examinations, obtaining unfair advantage, and falsification of records and official documents) as serious offenses against the values of intellectual honesty. The College is committed to enforcing the CUNY Policy on Academic Integrity and will pursue cases of academic dishonesty according to the Hunter College Academic Integrity Procedures.

Student performance will be evaluated by Weekly Assignments and Projects. While these are take-home projects and students are allowed to work in groups and answers to some of the questions are provided in the back of the textbook, students are expected to compose the final short answers, computer commands, and codes independently. There are virtually unlimited number of ways to solve a computational problem, as are ways and personal styles to implement an algorithm. Writings and blocks of codes that are virtually exact copies between individual students will be investigated as possible cases of plagiarism (e.g., copies from the Internet, text book, or each other). In such a case, the instructor will hold closed-door exams for involved individuals. Zero credits will be given to ALL involved individuals if the instructor considers there is enough evidence for plagiarism. To avoid being investigated for plagiarism, Do Not Copy from Others & Do Not Let Others Copy Your Work.

Submit assignments in Printed Hard Copies. Email attachments will NOT be accepted. Each assignment will be graded based on timeliness (10%), completeness (30%), whether executable or having major errors (20%), correctness of the final output (20%), algorithm efficiency (10%), and cleanness and readability in programming styles (10%).

Course Schedule (All Saturdays)

"Lecture slides" links will be available either during or before each lecture, in PDF.

January 29

Course Overview
Tutorial: UNIX Account, Tools, & Emacs [Lecture Slides]
Assignment #1:
- Unix Exercises (Part I on above page)
- Read Chapter 1

This is the header cell, which is always shown
This cell is not shown by default.

February 5

Chapter 1. Central Dogma & Wet Lab Tools [Lecture Slides]
Assignment #2. Part II Assignment 1 (above, Part II. 5-8); Problems (pg.31-32): 1.2, 1.3, 1.5, 1.7, 1.9, 1.10, 1.11

February 12

NO CLASS

February 19

Yozen will not be lecturing Chapter 6. Gene and Genome Structures [Lecture Slides] Tutorial: ORF Prediction using GLIMMER Assignment #3. Gene Identification

February 26

Appendix 1. Basic PERL [Lecture Slides] Assignment #4. Write a PERL script to print the reverse complementary strand of a DNA sequence (print the original, complement, and reverse complement strings; 5 pts). Questions & Problems (pg.234): A1.2 (5 pts)

March 5

Object-Oriented PERL & BioPerl [Lecture Slides] Assignment #5. BioPerl

March 12

Information Theory Tutorial: Sequence Logo Assignment #6. Information Contents at Intron-Exon junctions

March 19

Chapter 2. Data Search and Alignments Tutorial: Pairwise Alignment using BLAST & NUCMER Tutorial: Multiple Alignment using CLUSTALW Assignment #7. Questions & Problems (pg.54-55): 2.1, 2.2, 2.3, 2.4

March 26

Chapter 3. Molecular Evolution Assignment #8. Questions & Problems (pg.75-76): 3.1, 3.2, 3.3 (use first ten codons), 3.4, 3.5, 3.7

April 2

NO CLASSES

April 9

Chapter 4. Phylogenetics I. Distance Methods Tutorial: PROTDIST and NEIGHBOR using T-Rex Server Assignment #9. Questions & Problems (pg.95-96): 4.1, 4.3, 4.4, 4.7, 4.8

April 16

Chapter 5. Phylogenetics II. Character-Based Methods Tutorial: DNAML and bootstrap analysis using T-Rex Server Assignment #10. Questions & Problems (pg.115-116): 5.1, 5.2, 5.3, 5.4

April 23

Relational Database and SQL Tutorial: the Borrelia Genome Database Assignment #11. SQL-embedded PERL

April 30

Statistics Tutorial: Statistical Visualization using R Assignment #12. R Exercises

May 7

Chapter 6 (Gene Expression) & Chapter 8 (Proteomics) Tutorial: Array Data Visualization and Analysis Assignment #13. Gene Expression Data Analysis using R

May 14

Chapter 7. Protein Structure Prediction Assignment #14 (Final Comprehensive Project).

May 21

Final Project Due (TBA)