CSE 527 Computational Biology     [ Home Schedule Handouts Project ]



Syllabus (tentative)

  • Introduction (1 lecture)
    • Course logistics
    • Short intro to molecular biology
  • Introduction to probabilistic models for computational biology (3 lectures)
    • Bayesian network representation
    • Maximum likelihood estimation, expectation maximization algorithm
  • Systems biology (5 lectures)
    • Gene regulation basics, microarray data analysis
    • Learning regulatory networks
    • Systems genetics, network medicine
    • Finding regulatory motifs
    • Inferring signaling networks
  • Genetics (5 lectures)
    • Genetics basics, QTL mapping
    • Human genetics basics, genome-wide association studies (GWAS)
    • Haplotype reconstruction
    • Imputation, tagging SNP selection
    • Other issues in GWAS, two-point linkage analysis
  • Sequence analysis (3 lectures)
    • Sequencing
    • DNA, RNA sequence analysis
  • Computational cancer biology (2 lectures)

Dates for Assignments

  • Problem set 1: out 10/3. due 10/17.
  • Problem set 2: out 10/17. due 10/31.
  • Problem set 3: out 10/31. due 11/14.
  • Problem set 4: out 11/14. due 12/3.

Dates for Project Assignments

  • Project proposal: due 10/10. - extended to 10/17
  • Midterm report: due 11/7. extended to 11/14
  • Final report: due 12/14.
  • Final presentations or poster session: on 12/5. - postponed to 12/12

Late Day Policy

All assignments are due at the beginning of class (11:59am) on the assigned due date. We recognize that students may encounter unexpected circumstances and so require more flexibility in the course schedule. Therefore, each student will be granted a total of 3 free late (calendar) days that can be applied to every assignment, but not the final report submission.