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Program directors
Program directors
Program description
Program description
The MS program in computational life sciences introduces students to a burgeoning new field. Huge leaps in processing technologies have thrown open the doors for new research techniques and exciting opportunities for interdisciplinary collaborations, focusing heavily here on genomics data generation, analysis and interpretation.
Students are introduced to a suite of statistical tools and computational approaches that enable them to uncover correlations, glean new understanding, and help solve scientific problems.
Students examine many different types of data generated from a wide range of fields, including ecology, botany, evolutionary biology, neuroscience, molecular and cellular biology, and animal behavior. Students have the opportunity to investigate topics such as DNA, RNA, protein, imaging, conservation and even historical data from long-term ecological research sites.
Finally, students explore the ethical implications of collecting, analyzing and sharing the results of computational life sciences data.
Degree requirements
Degree requirements
The current degree requirements are below. Remember you are required to fulfill the requirements from the academic year you were admitted. Please refer to the handbook from your year of admission as needed.
Total: 30 credit hours, including a capstone or applied project
Required Core Section (1 credit hour)
(1) BIO 511 Big Data in Context: Ethics, Policy, History and Philosophy
OR
(1) BIO 610 Introduction to Responsible Conduct of Research (RCR) in Life Sciences
Restricted Electives Section (18-20 credit hours)
*We highly recommend that students take a computing in life science restricted elective and a biology restricted elective in their first semester.
A. Computing Area (6-7 credit hours)
B. Statistics and Mathematics Area (6-7 credit hours)
C. Biology Area (6 credit hours)
Refer to the CLS MS Course Offering Guides below for an extensive list of course options that fit into each area.
Open Electives Section (6-8 credit hours)
Refer to the CLS MS Course Offering Guides below for an extensive list of approved elective options.
Culminating Experience Section (3 credit hours)
(3) BIO 593 - Applied Project
An applied project is best when you will apply methods learned during the degree to some well-defined problem; for example, carrying out a certain suite of computational analyses to a dataset. (A formal proposal and Program Director approval is required well ahead of your final semester)
(3) BIO 597 - Capstone
A capstone is best for more open-ended writing tasks; for example, performing a literature review of computational software available for a particular type of analysis and writing a description/evaluation of this literature.
Course offering guides
Course offering guides
Use the live Google Sheet below to narrow down your course search each semester and ensure that the courses you are selecting align with the appropriate degree requirements.
Online
Online
On campus
On campus
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