01:447:302 Quantitative Biology & Bioinformatics
This course is a computer-based lab course.
All Genetics majors must complete a lab course requirement to complete the degree requirements. The lab course requirement can be satisfied by taking either this course or 01:447:315 or 01:694:214 or 01:694:215.
Spring Term Only, M and Th 10:20-1:20
Gen Bio Lab 01:119:117 or 01:119:102 and Genetics 01:447:380 or Genetic Analysis I 01:447:384
This course is limited to Genetics majors. Other students can be added by special permission number pending computer space availability.
Quantitative Biology and Bioinformatics is a computer-based laboratory course that introduces students to the use of computers in biological research. Instruction is given in introductory computer programming while developing applications and analyses for problems in genetics and molecular biology. Classes consist of a mixture of lecture and computer-based exercises, as well as time for students to work on assignments. The course provides the introductory skills needed to conduct basic computational research in the life sciences, including many aspects of computer programming and data analysis. This course is particularly aimed at students who plan to pursue research careers, attend graduate or medical school, or enter the biomedical/research workforce.
Class will meet in a computer lab for two double periods (160 minutes) per week. No prior programming experience is required. However, because computer programming concepts can be difficult for some students to master, we strongly recommend that you complete an hour or more of online Python tutorial before the start of class, to get a sense of whether a programming course is a good choice for you. More info provided on the course SAKAI website.
Course Satisfies Learning Goals
1. Knowledge specific goals: Know the terms, concepts and theories in genetics.
2. Integrate the material from multiple courses and research. That is, to think holistically and to see the whole as well as the parts.
Core Curriculum Learning Goals met by this course:
IRT y: Employ current technologies to access information, to conduct research, and to communicate findings.
IRT z. Analyze and critically assess information from traditional and emergent technologies.
Exams, Assignments, and Grading Policy
Students will be assigned weekly projects based on current material. The final grade is based on the grades received on these projects, quizzes, and a final exam.
A basic text (print or digital) in Python programming is recommended. Other materials will be obtained online.
If this course is closed, please use the following link to add your name to the wait list: Wait List Sign Up for Spring 2017 Courses .
If you have any questions, please contact the Department of Genetics Undergraduate Education Office in Nelson Biological Laboratories Room B416 or call 848-445-1146.
Dr. Linda Brzustowicz
Dr. Kevin Chen
Dr. Vikas Nanda
Dr. Wilma Olson
** All information is subject to change at the discretion of the course coordinator.