Foundations of Bioinformatics and Systems Biology

Bioinformatics - the application of computational and analytical methods to biological problems - is a rapidly maturing field that is driving the collection, analysis, and interpretation of the avalanche of data in modern life sciences and medical research.

Description: Foundations of Bioinformatics and Systems Biology (BIOINF525) provides an introduction to the principles and practical approaches of bioinformatics as applied to genes and proteins.

The complete course is comprised of three modules covering (1) Foundations of Bioinformatics; (2) Statistics in Bioinformatics; and (3) Systems Biology. Each module is 1 credit and can be registered for separately.

Module 1: 	 January 12 – February 5 	(four lectures and four labs).
Module 2: 	 February 9 – March 18 		(five lectures and five labs).
Module 3: 	 March 22 – April 15 		(four lectures and four labs).

Schedule: In addition to Tuesday lectures students should attend one lab session per week. Please note that students must register under either the Session I (Thursday) or Session II (Friday) lab times that they wish to attend throughout each module. A detailed syllabus with topic outlines is available for download.

Lectures:	 Tuesdays 2:30 - 4:00 PM, Rm. 2062 Palmer Commons Bldg. 

Labs:		 2:30 – 4:00 PM Thursdays (Session I) or 
		 10:30 - 12:00 PM Fridays (Session II).
 		 Rm. 2036 Palmer Commons Bldg. 

Prerequisites: A familiarity with basic biomedical concepts and basic knowledge of computer usage. No programing skills are needed.

Requirements: Students should bring their own WiFi enabled laptop to lectures to fully benefit from the hands-on components of each lecture. Please see our laptop setup instructions for further details. Computers will be provided for lab sessions.

Objectives: Students completing this course will be able to apply leading bioinformatics tools and statistical techniques to address biological questions. Students will also obtain fundamental R programming skills necessary for analyzing data in the life sciences. Our broader goal is to point towards perspectives that bioinformatics can expose for the integration and analysis of complex biological information.

Grading: Satisfactory/unsatisfactory grading will be based on a combination of lecture and lab involvement together with weekly homework and quiz assignment performance.

Why take this course?: Praise for the 2015 class from official student evaluations.

Dr. Barry Grant
Department of Computational Medicine and Bioinformatics
2055 Palmer Commons Building
University of Michigan