This course may also be used to fulfill the elective requirements of the Biological Sciences major.
Offered: Fall T/H4 (Tues/Thurs 1:40 - 3:00 PM) SEC-210
Prerequisites: General Biology 01:119:115-116 or 01:119:101-102 and 01:640:135 or 01:640:151
Course Description: This course is targeted at sophomores and juniors interested in learning the mathematical techniques useful in the biological sciences in the emerging era of computational genomics. The course will cover mathematical methods and tools of computational biology, including Probability Theory, Bayes Theorem, the Binomial, Poisson and Normal distributions, limit theorems, error analysis, tests of statistical significance, parameter estimation, curve fitting, sampling techniques, random number generation and Monte Carlo methods. We will also study mathematical methods useful in the analysis of sequencing and microarray data, such as sequence alignment, phylogeny inference, methods to infer population structure, selection and human migration patterns, methods used in GWAS studies, and methods to identify functional SNPs and pathways. Concepts will always be explained in the simplest possible way and in the context of biological examples, many of which will be worked out in detail in class. We will often use Matlab as a tool to analyze and plot data, do statistical inference and perform numerical simulations. The overall goal of this course is to give the students the mathematical tools and programming skills necessary to analyze and interpret biological and biomedical data correctly and with confidence.
Course URL: Sakai
Course satisfies Learning Goals
MBB Departmental Learning Goals: 1, 2,and 3
Course Learning Goals: The overall goal of this course is to give the students the mathematical tools and programming skills necessary to analyze and interpret biological and biomedical data correctly and with confidence.
Exams, Assignments, and Grading Policy
40%: Homework. Homework will be handed out in class each week and is due the following week.
20%: In class-Midterm
40%: In class-Final
1. Notes for each lecture will be handed out at the end of the class. If you attend all classes and pay attention, these should be sufficient.
2. Text book for statistical methods: Mathematical Statistics and Data Analysis, Second edition: John A. Rice. The book is available as a DjVu document and will be emailed to all students. You will need to install DjVu Viewer on your computer to see its contents.
3. Text book for Matlab (recommended but not required): Computational Statistics Handbook with MATLAB, Second Edition (Chapman & Hall/CRC Computer Science & Data Analysis) by Wendy L. Martinez and Angel R. Martinez (Hardcover - Dec 20, 2007).
4. Software: Please make sure you have MATLAB installed on your computer, including the MATLAB Statistics Toolbox.
Course Closed? Enrollment is limited to 50 students.
** All information is subject to change at the discretion of the course coordinator.