Computational Biology:
G22.3033.004
- Lecturers:
-
Professor
B. Mishra
with
Dr. L. Parida and
Dr. R. Daruwala
Office Hours: By appt.
Office Phone: 212.998.3464
Email Address: mishra@nyu.edu
- Day and Time:
-
Tuesdays, 5:00-6:50pm EST, Room 101, 251 Mercer St.
- Credits for Course:
-
3
- Prerequisites:
-
Mathematical Maturity, Combinatorics, Statistics and
Algorithms Design
- Syllabus:
- 1. Introduction to Biology: Genome; Central Dogma; RNA, DNA, Proteins; and Cell
- Challenges for computational biology:
- Alignments (sequence alignments, structure alignments)
- Pattern Finding (motifs, gene prediction, cis-regulatory elements)
- Overlap Detection and Contigs
- Structure Prediction (Protein Folding & RNA secondary structure)
- Classification (Protein families, gene families)
- Phylogeny Analysis
- (databases available)
- 2. & 3. Introduction to Computer Science, Statistics; Algorithms (Varun ) and data structures (trees)
- Dynamic programming
- Complexity: P and NP (eg- multiple sequence alignment)
- Heuristic methods, neural networks, simulated annealing, genetic
algorithms
- Statistical distributions, models, estimation
- Bayesian Inference
- EM Algorithms, Metropolis, Gibbs Sampler, MCMC
- Hidden Markov Models
- Supervised learning, SVM
- 4. & 5. Pattern Discovery & Sequence Alignment (applications)
- Exact Matching, Approximate Matching
- Exact & Approximate Pattern discovery
- Pair-wise alignment (Needlman-Wunsch, Smith-Waterman)
- Multiple sequence alignments (heuristics)
- 6. Mapping, Sequence Assembly
- Sanger sequencing,
- cloning, clone overlaps
- interval graphs
- contig algorithms
- ocean-islands (Lander Waterman model)
- 7. Proteomics (Structure Prediction)
- Introduction (primary, secondary structures)
- Ab-initio models for prediction
- Homology based, threading
- Geometric shape matching (docking)
- 8. & 9. Transcriptomics
- Gene expression
- Microarray data analysis (supervised & unsupervised)
- Motif detection in promoter sequences
- 10. Metabolic & Regulatory Pathways
- Kinetic mass action models (eg LAC operon)
- Trajectory Analysis
- Model Reconstruction & Validation
- 11. Evolution
- Models of evolution
- Evolutionary distances
- Phylogeny trees
- 12. Genetics, SNPs & Association Studies
- Coalescent trees and haplotypes
- SNP phasing (perfect phylogeny & statistical methods)
- Required Text(s):
-
-
Bioinformatics: A Practical Guide to the Analysis of Genes and
Proteins,
by Andreas D. Baxevanis and B. F. Francis Ouellette ,
Wiley-Interscience,
ISBN: 0471383910.
-
Statistical Methods in Bioinformatics,
by Warren J. Ewens, Gregory R. Grant,
Springer Verlag; 1st edition (April 20, 2001),
ISBN: 0387952292.
-
Structural Bioinformatics
by Philip E. Bourne and Helge Weissig,
John Wiley & Sons,
ISBN: 0471201995.
- Recommended Text(s):
-
-
Molecular
Biology Notes on the web
-
Introduction to Computational Molecular Biology,
by Setubal & Meidanis, PWS Publishing Company,
ISBN 0-534-95262-3.
-
Principles of Genome Analysis and Genomics,
by S.B. Primrose & R.M.Twyman,
Blackwell Science, ISBN 1-4051-0120-2.
- Midterm Date:
-
No Midterm.
- Final Date:
-
Class Project.
- Homework(s):
-
Class Presentation.
Bud Mishra
September 1 2003