Course Descrption-Bioinformatics This course will introduce biotechnology students to
important concepts in bioinformatics, including information flow in biological systems and use
of sequence and structure databases in research and drug discovery. Algorithms making use of
sequence similarity to infer evolutionary relationships, and the use of evolutionary relationships
to deduce structural and functional information, will be explored. The underlying concepts and
methods as well as the use of existing programs and databases will be stressed. Computer
exercises will include pairwise and multiple sequence alignment, primer design for polymerase
based applications, basic phylogeny, and introductory structural model building.
Syllabus
Biotechnology 4490 Bioinformatics I: Sequence analysis Spring 2008
Prerequisites: Genetics
Class meets 8-9:15 AM in 214Science
John C Salerno, Professor
X6177
Office:336 Bldg 12 (Science)
jsalern3@kennesaw.edu
Office Hours: TBA
1/8
1/10
1/15
1/17
1/22
1/24
1/29
1/31
2/5
2/7
2/12
2/14
2/19
2/21
2/26
2/28
3/11
3/13
3/18
3/20
3/25
3/27
4/1
4/3
4/8
4/10
Introduction
Information in Biology
Molecular Biology and Biological Chemistry
Molecular Biology and Biological Chemistry
Databases and Web Sites
Searches and Alignments: Scoring and Gaps
Searches and Alignments: Needleman Wunsch and Dynamic Programming
Searches and Alignments: Smith Waterman
Searches and Alignments: BLAST
Searches and Alignments: FASTA
First Exam
Substitution & Evolution
Substitution & Evolution
Substitution & Evolution
Molecular Phylogeny
Trees
Distance Methods
Maximum Likelihood
Parsimony
Phylogenetics
Second Exam
Prokaryotic Genomes
Prokaryotic Genes
Eukaryotic Genomes
Eukaryotic Genes
Expression
4/15
4/17
4/22
4/24
A bit about Proteins: structure prediction
Protein classification
Drug Design
Simulation
The course will introduce biotechnology students to important concepts in bioinformatics,
including information flow in biological systems and use of sequence and structure databases in
research and drug discovery. Algorithms making use of sequence similarity to infer
evolutionary relationships, and the use of evolutionary relationships to deduce structural and
functional information, will be explored. The underlying concepts and methods as well as the
use of existing programs and databases will be stressed.
Text: Krane and Raymer, Fundamental Concepts of Bioinformatics, Benjamin Cummings
Most of the lectures correspond closely with the first 8 chapters. Buy and read the book. I do
talk about other things; if you elect to miss class, it’s your responsibility to get notes.
Expected Outcomes:
1) Students will be familiar with basic concepts of information flow in biology.
2) Students will become familiar with the uses and basic structure of some biologically
important databases (e.g., GenBank, SwissProt)
3) Students will develop an understanding of how some of the critical algorithms in
bioinformatics work, and be able to apply these algorithms to the investigation of
experimental problems
4) Students will understand the central role of evolutionary concepts.
5) Students will become conversant with the basic ideas of structure and function
prediction.
6) Students will learn basic concepts of simulation as a way of interpreting experimental
results.
Grading: There will be two in class exams and a final. In addition, there will be a class project,
which will result in individual and independently written papers, due on the second last class of
the semester. Periodic homework problem sets will be given out to assist you in developing
facility with difficult material. It is important to do them or you won’t do well on the exams.
Exams I & II
15% each
Final
30%
Class Project
30%
Homework and participation 10%
Disabilities: Any student with a documented disability needing academic adjustments is
requested to notify the instructor as early in the semester as possible. Verification from KSU
disAbled Student Support Services is required. All discussions will remain confidential.
Academic Integrity: I don’t tolerate dishonesty in my courses or in my lab. Do your own work
and don’t cheat. Minimum penalty for any form of cheating is F on the exercise in question, and
I will fail you for the course for a serious offense. You can demand a formal hearing by the
University Judiciary Program, but that might result in suspension or expulsion. If you intend to
cheat, don’t take my course. If you get desperate, come in and talk to me instead. See also:
http://www.kennesaw.edu/universitycollege/integrity.html
http://www.kennesaw.edu/judiciary/code.conduct.shtml#xi