Computational Molecular Biology

Biochemistry 218 - Biomedical Informatics 231

Doug Brutlag

Course Description

Computational Molecular Biology (Biochem 218) is a practical, hands-on approach to the field of computational molecular biology. The course is recommended for both molecular biologists and computer scientists desiring to understand the major issues concerning representation and analysis of genomes, sequences and proteins. Various existing methods will be critically described and the strengths and limitations of each will be discussed. There will be practical assignments utilizing the tools described. While no computer experience or programming skills are required, prior exposure to personal computers, e-mail, and the Internet are essential. All homework and coursework must be submitted electronically. Prerequisites include an introductory molecular biology course at the level of Biology 41 or permission of the instructor. Students who have not had a course in molecular biology may acquire the necessary background by reading either Stryer's Biochemistry (5th edition by Berg, Tymoczko and Stryer) or Lewin's Genes IX.

Course Requirement

There will be 7 homework assignments utilizing the tools described in the lectures. All homework and final projects will be submitted in electronic form, as e-mail or e-mail attachments. A final paper will be required for the course that critically and constructively analyzes one of the areas presented in the course. The final project may also present a novel application of existing tools or the development of some new or improved method. The final projects will be due Sunday, December 13, at midnight. There will be no extensions of this deadline. The homework will count for 35% of the final grade and the project will count for 65%.

Examples of Previous Final Projects

 Academic Year 2009-2010

The course will be available online during the Autumn and Spring Quarters and will be taught live in the Winter Quarter.

Registration

Registration is limited to 50 students. On campus students must register with the registrar via AXESS.  Off campus students must register with the Stanford Center for Professional Development.Students receiving a grade of B or better in this course may use this grade as partial completion towards the Stanford Bioinformatics Certificate program.

Auditors

Anyone on Stanford Campus or participating in Stanford Overseas Campus may audit the lectures on the Internet via Stanford Online during a quarter this course is being taught. All lectures are recorded and made available via streaming video (see below for instructions). There is no limit on the number of auditors. Stanford Online lectures are available 24 hours a day, 7 days a week. The only requirement is that the auditors must have a valid SUNET ID in order to view the lecture. Auditors will also be permitted to attend the classes as long as there are seats available. No homework will be permitted and no grade will be awarded for auditors.

Teaching Assistants and Staff

Dan Davison (davisond@stanford.edu) is the teaching assistant for the course and will answer questions about the homework and course content. Lee Kozar (kozar@stanford.edu) is the Director of the Bioinformatics Resource at Stanford and is in charge of the computing facilities including software and databases that will be used for the homework. Questions concerning the programs, databases and other computing resources used in the course should be addressed to him. Doug Brutlag (brutlag@stanford.edu) is the Administrator for the course. You should contact him for all administrative needs such as registration priority, web page problems, student status, etc.

Lecture Syllabus

(These videos require QuickTime and will run on both Windows and Macs)

Topic

Lecturer

Video
Slides
Sept. 22

Genomics & Bioinformatics

Doug Brutlag

Video
Slides
Sept. 24

Bibliographic and Full Text Journal Access

Doug Brutlag

Video
Slides

Sept. 29

Genome Databases

Doug Brutlag

Video
Slides

Oct. 1

Molecular Biology Databases on the Web

Doug Brutlag

Video
Slides

Oct. 6

Pattern Matching with Consensus Sequences

Doug Brutlag

Video
Slides

Oct. 8

Quantitative & Probabilistic Pattern Matching

Doug Brutlag

Video
Slides

Oct. 13

Sequence Alignment

Doug Brutlag

Video
Slides

Oct. 15

Rapid Sequence Similarity Search

Doug Brutlag

Video
Slides

Oct. 20

Near-Optimal Sequence Alignments

Doug Brutlag

Video
Slides

Oct. 22

Multiple Sequence Alignment

Doug Brutlag

Video
Slides

Oct. 27

Distance Based Phylogenies

Doug Brutlag

Video
Slides

Oct. 29

Sequence Blocks & Profiles

Doug Brutlag

Video
Slides

Nov. 3

Protein Sequence Motifs

Doug Brutlag

Video
Slides

Nov. 5

Protein Structural Motifs

Doug Brutlag

Video
Slides

Nov. 10

Clustering and Functional Analysis of Coordinately Regulated Genes

Gavin Sherlock

Video
Slides

Nov. 12

Discovering Transcriptional Regulatory Signals

Doug Brutlag

Video
Slides

Nov. 17

Ultraconservation in the Human Genome

Gill Bejerano

Video
Slides

Nov. 19

Pathway Bioinformatics

Peter Karp

Video
Slides

Homework Assignments

Number
Date Assigned Homework Date Due
1
September 22 Introduction and short resumé September 29
2
October 1 Accessing molecular biology databases October 8
3
October 8 Sequence motif scanning for functional analysis October 15
4
October 15 Adjusting alignment parameters October 22
5
October 22 Sensitivity/specificity analysis of sequence similarity search October 29
6
October 29 Comparison of phylogenetic methods November 5
7
November 5 Building protein families and sequence motifs November 12
September 22 Final Project December 13

 

You may also access videos on the SCPD Web site

(The SCPD Videos run on both Windows and Macs but require

Flip4Mac media components to be viewed on a Macintosh)

Tutorials

Topic

Lecturer

Intro to the GCG SeqWeb Interface

Lee Kozar

Literature Search Techniques

Lee Kozar

Sequence Comparison and Demo of GCG SeqWeb BestFit and Gap

Lee Kozar

Progressive Pairwise Alignment Algorithm and Its Use by the SeqWeb BestFit Program

Lee Kozar

Phylogenetic Analysis - Intro to Distance Methods to Study Evolutionary Relationships

Lee Kozar

Bioinformatics Week Videos

https://cmgm.stanford.edu/classes/EBI-NCBI/videos/

Bioinformatics Resource Courses

http://cmgm.stanford.edu/classes/

** Last Updated August 19, 2009**

CC Doug Brutlag