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Bioinformatic Computing - Syllabus

BIOS60579
CSE 60532
Bioinformatics Computing
Fall  Semester 2005

Brief Description:
Bioinformatics is the study of the structure and function of genes and proteins through the use of computational analysis, statistics, and pattern recognition and the use of databases, search and web-based interfaces to store, annotate and retrieve gene, protein and other information.

Texts:
Jones/Pevzner, An Introduction to Bioinformatics Algorithms, MIT Press, 2004, ISBN: 0-262-10106-8

Mount, Bioinformatics: Sequence and Genome Analysis, Cold Spring Harbor Laboratory Press, 2nd Edition, 2004, ISBN: 0-87969-712-1

Instructors:

Frank Collins
Department of Biological Sciences
313 Galvin Life Science
Notre Dame, IN 46556
574 631 9245
frank@nd.edu

Greg Madey
Department of Computer Science and Engineering
350 Fitzpatrick Hall
574 631 8752
gmadey@nd.edu

Teaching Assistants:

John Tan
jtan1@nd.edu

Deborah Thomas
dthomas4@nd.edu

Course Goals:  To introduce the student to the biology of bioinformatics and to understand how computer science algorithms solve problems and discover new knowledge in genomics, proteomics, metabolomics, transcriptomics, and other omics.

Pre-Requisites: For computer science students, computer programming skills, graduate status; for Biology students, one or more courses in genetics and/molecular biology, and graduate status.

Topics:      

1.  Introduction to the Genome  
     DNA/RNA
     Amino Acids
     Proteins
2.  Information flow from the Genome  
     Genes
     Transcription
     Translation
3.  Other Information in the Genome   
4.  Web-based information systems
5.  Bioinformatics programming/modeling  
     Languages
     Computational analysis tools
     Algorithms/Computational Complexity
     Statistics/Data Mining
     Pattern matching techniques
6.  Databases/Data modeling    
     Database theory
     Design/Schema
     Ontologies
     Search/Queries
     Data warehouses
7.  Data visualization     
8.  Alignment of a pair of sequences   
9.  Dotplots      
10.  BLAST and FASTA    
11.  Global sequence alignments   
12.  Multiple sequence alignments   
13.  Amino acid alignments    
14.  Amino acid searches    
15.  Hidden Markov model searches   
16.  Protein folding     
17.  Protein domains     
18.  Protein comparisons, domains and protein families
19.  Ab initio gene prediction    
20.  Identification of regulatory regions  
21.  Genome sequencing and assembly  
22.  Genome annotation:  automated pipelines 
23.  Genome annotation: manual (Apollo)  
24.  Genome comparison    
25.  RNA secondary structure    

Computer Usage: Homework assignments will require programming

Laboratory Usage: None

Grading:   Homework Assignments and Projects  55%
   Final Exam      20%
   Mid-term Exam     10%
   Class Participation     15%

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