Intro to Bioinformatics (BioE 480)
This is the general introductory course in bioinformatics. The main techniques covered in this course are related to sequence analysis and include: gene identification, genome sequencing, sequence comparison, database searching, and phylogenetic tree analysis. Molecular biology is also introduced including: the central dogma of molecular biology, DNA sequences, and protein sequences. Students will be introduced to all of the biology necessary to understand the applications of bioinformatics algorithms and software taught in this course.
Topics covered:
- Sequence comparison algorithms and the software program FASTA as well as related programs
- Sequence database searching with BLAST, PSI-BLAST, and HMMER
- Functional database searches with GO and PFAM for gene identification and functional assignment
- Biology database design using SQL/mySQL
- Programming to solve text processing another bioinformatics task with perl, and learning how to use the bioperl database to search for the available programs;
- Phylogenetic analysis with the program PHYLIP.
These programs are widely used in industry and academia.
Syllabus:
- Lecture 1: Intro to course with review of relevant molecular biology
- Lecture 2: Review of relevant molecular biology
- Lecture 3: Pairwise sequence alignment
- Lecture 4: Scoring Matrices
- Lecture 5: Multiple Sequence Alignment
- Lecture 6: Statistical Methods in Sequence Analysis
- Lecture 7: Introduction to Hidden Markov Models
- Lecture 8: Using Hidden Markov Models for Sequence Analysis
- Lecture 9: Statistical Methods in Bioinformatics
- Lecture 10: Database Search (1.5 lectures)
- Lecture 11: Microarray Data Analysis (1.5 lectures)
- Lecture 12: Introduction to Phylogenetic Analysis
- Lecture 13: Phylogenetic Analysis
- Lecture 14: Gene Finding
- Lecture 15: Whole Genome Analysis
- Lecture 16: Genomic Circuits
- Lecture 17: Protein Structure and Prediction
- Lecture 18: Protein Secondary Structure Prediction & Homology Modeling
- Lecture 19: Protein Folding
- Lecture 20: Drug Design, Discovery, and Docking
- Lecture 21: RNA Secondary Structure Prediction
We will normally post 2 lectures per week (on Mondays).
Prerequisites:
- Basic theory and uses of probability. See section 1.3 in the book “Biological Sequence Analysis” by R. Durbin et al. (ISBN: 0-521-62971-3) for a review.
- Some programming experience and skill using Perl, C++, or Java. See “Beginning Perl for Bioinformatics” by O’Reilly. (ISBN: 0-596-00080-4) for a review.
Textbook:
Mount, D.W., Bioinformatics: Sequence and Genome Analysis, Second Edition, CSHL Press, ISBN 0-87969-712-1
Grading:
- Homework
- worth 100 points will be assigned each week.
- The homework will be posted on Wednesday and will be due the following Wednesday.
- For any week, we may post homework early. This will not affect the due date of the homework.
- Late homework will be accepted until the first Friday following the due date with a penalty of 20 points per day late. Homework will not be accepted after Friday.
- Comprehensive project (due on the same day as the final exam)
- Midterm and final exams