CISC 841 Bioinformatics (Spring 2006)
( under construction)
2/7 Lec 1: Overview of the course (note)
- Course objectives and logistics
- A glimpse into the field
- Reading:
- Intro to bioinformatics for computer scientists by Cohen (PDF)
- Bioinformatics Overview by Gerstein (PDF)
2/9 Lec 2: A primer to molecular biology (slides)
- The central dogma: DNA -> mRNA -> Protein
- Biological data acquisition (high-throughput) techniques: Cloning, PCR, Shotgun sequencing, DNA microarray, Yeast 2 hybrid
- Systems biology
- Reading:
- A primer on molecular biology by Alexander Zien (PDF)
- Molecular biology for computer scientists by Larry Hunter (PDF)
2/14 Lec 3: Homology detection: sequence similarity based approaches
- Pairwise alignment
- Dynamic programming: Needleman-Wunsch algorithm
2/16 Lec 4: Pairwise alignment
2/21 Lec 5: Gap penalty
- General gap penalty: convex
- Gap penalty: Affine
- Gotoh algorithm
2/23 Lec 6: Refinements for pairwise alignments
- Linear space
- FASTA and BLAST
2/28 Lec 7: Use similarity search for annotations
- E-value, p-value
- Sensitivity, specificity, correlation coefficient, and ROC
- Multiple sequence alignments
- Homework 1 is out.
3/2 Lec 8: Profiles
- Progressive approach to MSA (CLUSTALW)
- Position specific score matrix
- Markov chains
- MCMC Metropolis algorithm
- Hidden Markov models
- A simple model for gene prediction
- Viterbi algorithm
3/9 Lec 10: HMMs:
- Membership classification (Likelihood)
- Forward algorithm
- Log transformation for Viterbi algorithm
- HW1 is due and HW2 is out.
3/14 Lec 11: HMMs:
- Viterbi training
- Baum-Welch algorithm
- Maximum Likelihood
- Bayesian approach, regularization, and pseudocounts
- Dirichlet distribution, and mixtures
3/16 Lec 12: Kernel methods (Lecture notes)
- A primer on kernel methods by Vert (PDF)
- SVM Applications in Computational Biology by Noble (PDF)
3/21 Lec 13: Kernel methods
3/23 Midterm
3/28 (Spring break)
3/30 (Spring break)
4/4 Class canceled
4/6 Lec 14: Biological Networks (Slides)
Interesting and related papers: