Instructor: Shaojie Zhang
Lectures: M/W 3:00-4:15 pm HEC 110
Office hours: M/W 1:00-2:00 pm HEC 311
Syllabus: The course will concentrate on computer science aspects of computational molecular biology and will emphasize the recent advances and open problems in the area.
The computational techniques will include algorithms, graph theory, combinatorics, machine learning, etc. Many important bioinformatics topics will be used as examples to illustrate how the formulation and solution of a computer science problem can help to answer a biological question.
This course is designed for computer science graduate students. No biology knowledge is required.
Graduate students with either biology or physical/computer science backgrounds who have taken a fundamental bioinformatics course are also welcome to take this course.
Preliminary topics to be covered: 1. Introduction to algorithms 2. Exact string matching, Data structure: Suffix tree 3. Suffix tree: applications 4. Mismatch tree and the motif finding problem 5. Breaking problems down: dynamic programming 6. Combinatorial search: intractable problems 7. Integer programming; Reductions 8. Graph algorithms: trees 9. Haplotyping via perfect phylogeny 10. Comparing trees 11. De Bruijn graph; Eulerian graphs 12. Minimum Spanning trees; Shortest paths 13. Matching problems; Network flow 14. Breakpoint graph 15. Set cover and set packing 16. Graph-based clustering 17. Heuristic algorithms
Assignments: We will have 4 take-home assignments.
Grading: Assignments (40%), Midterm exam (25%), Final exam (25%), Attendance (10%).
Topics and Tentative Agenda:
|1||08/24||Introduction to algorithm|
|08/26||Exact string matching|| Dan 2.3, Dan 1.4
|2||08/31|| Z-value, Suffix trees |
Assignment 1 (Due 09/14)
|Dan 1.4, Dan 6|
|09/04||Suffix trees|| Dan 6
|3||09/07||No Class (Labor Day)|
|09/09||Suffix trees||See above|
|4||09/14||Mismatch tree|| CMB 8.6
|09/16||Dynamic Programming|| CMB CMB 6.2 and 6.3
|5||09/21||DP Applications: RNA folding, complicated parameters||mfold|
|09/23|| DP Applications: RNA alignments with guiding tree |
Assignment 2 (Due 10/7)
|6||09/28||DP Applications: Pseudoknotted RNA alignments||pseudoknot|
|09/30||DP Applications: RNA folding, a different formulation||RNAscf|
|7||10/05||DP Applications: Spliced sequence alignment||CMB 9.4|
|10/07||NP-hard problem and multiple sequence alignment|
|8||10/12||Algorithmic problems related to phylogenetic trees-1|
|10/14||Mid-term Exam (take-home)|
|9||10/19||Algorithmic problems related to phylogenetic trees-2 (Fitch Algorithm)||See above|
|10/21|| Algorithmic problems related to phylogenetic trees-3 (perfect phylogeny) |
Assignment 3 (Due 11/04)
|10||10/26||Algorithmic problems related to phylogenetic trees-4 (SNP)||See above||PPH|
|10/28||Algorithmic problems related to phylogenetic trees-5 (SNP and Haplotyping)||See above||PPH|
|11||11/02||De Bruijn graph and Eulerian graph-1||CMB 5|
|11/04||De Bruijn graph and Eulerian graph-2 (fragment assembly)||See above||CMB 5|
|12||11/09||Genome rearrangements and breakpoint graph-1||CMB 10|
|11/11||No Class (Veterans Day)|
|13||11/16|| Genome rearrangements and breakpoint graph-2 |
Assignment 4 (Due 11/30)
|See above||CMB 10|
|11/18||Computational Problems in RNA-seq data analysis|
|14||11/23||Computational Proteomics (Spectrum Graphs and Spectral Alignment)-1||CMB 11|
|11/25||No Class (Thanksgving Day)|
|15||11/30||Computational Proteomics (Spectrum Graphs and Spectral Alignment)-2||See above||CMB 11|
|11/02||omputational Proteomics (Spectrum Graphs and Spectral Alignment)-3||See above||CMB 11|
We are always looking for motivated students. If you are looking for research projects, please get in touch.