Course Description:Due to the large volume of data generated by genome sequencing and cellular measurements of gene expression changes, computer science and mathematics have profoundly changed the science of modern biology. Computational and mathematical methods are now critical to the development of both experimental and analytical tools in genomics. This course will provide students from all disciplines with an introduction to some of the basic mathematical and computational tools that have been developed to analyze, model and understand these biological data. The mathematical topics will consist of discrete mathematics and probability; however, the emphasis of the course is on algorithmic techniques applied to problems motivated by molecular biology and genetics. In particular, the course will focus on sequence alignment algorithms, hidden Markov models, and computational approaches to genetic and physical mapping, DNA sequencing, and phylogenetic reconstruction. Computer lab sessions will be incorporated to implement some of the main algorithms and introduce a variety of commonly available software packages for problem solving. For example, NCBI databases, tools such as BLAST, and software packages for tree reconstruction will be covered.
Instructor: Sharon Crook, Dept. of Mathematics and Statistics & School of Life Sciences
Office: GWC 648
Instructor Website: http://math.la.asu.edu/~crook
There is no textbook!
Prerequisites: Because this is an upper level course, we require that students complete MAT 270, MAT 210, MAT 251, MAT 243, or STP 220 prior to this course. However, all mathematical skills needed during the course will be covered in class.
Additional Information: This course satisfies the general studies computer science requirement for students in the College of Liberal Arts and Sciences. This course also satisfies the MAT 351 requirement for students in the MBB Program.
Assignments: All homework and projects must be neatly done. No late assignments will be accepted. Make-up exams require permission in advance with a Doctor's excuse in the case of illness. You may work together on homework and projects but you must do the work cooperatively. For some of the assignments, you will be required to work in groups.
Grading scale: A: 90% and above, B: 80-89%, C: 70-79%, D: 60-69%
Grading: Homework and Classwork: 40%, Projects (3 or 4): 40%, Final Exam: 20%
Honors Students: Let me know if you would like to sign a contract for a project as part of the Honors Curriculum.
If you wish to request an accommodation for a disability, please contact me as early as possible in the semester.
Some lecture topics:
Introduction to computational molecular biology
Introduction to the computer lab and sequence data
Algorithms and pseudocode
Dynamic programming for sequence alignment
Multiple sequence alignment algorithms
BLAST and FASTA
Gene finding algorithms (hidden Markov models) and software
Basics of phylogenetic reconstruction algorithms
Graph theory basics
Sequence assembly algorithms
Gene expression databases
Clustering algorithms and software