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

• Log-odds scoring (where did BLOSUM62 come from?)
• Dynamic programming: Smith-Waterman algorithm

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

3/7 Lec 9: HMMs: (Tutorial by Rabiner, Tutorial by Petrushin Part I & Part II)

• 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:

• Bioinformatics scientists versus technicians, by Pavel Pavzner. An editorial in Journal Bioinformatics PDF
• "Antedisciplinary" Science by Sean Eddy. PDF
  
• Bioinformatics market explosive
• Genome book
• Molecular Biology of The Cell 4th Edition, by Alberts et al.
• Intro to Perl by Patrick Ryan (PDF)
• Perl reference (PDF)
• Perl Cookbook