Unlock the secrets of the next generation of biological data. Advances in sequencing, sensing, racking and computing have led to both an explosion of biological data, and the urgent need for biological data scientists to work with that data – both in industry and in academia. This biological data science master’s degree program sits at the intersection of biology, computing, mathematics, and statistics, providing students in any of these disciplines the unique opportunity to develop an integrative skill set to analyze and understand these new biological data sets.
The MS program in biological data science provides students with real-world training at the interface of the natural and mathematical sciences. Students learn to manipulate "Big Data", including the generation and analysis of data using statistical and computational toolsets. Students will use their analytical skills in ecological, environmental, toxicological and other biological applications. The program incorporates multiple levels of experiential learning to ensure students gain critical-thinking skills on top of core competencies. Students will be ready to enter one of the fastest-growing job markets, work with consulting firms and government agencies as well as non-governmental organizations, or go on to seek advanced professional or graduate degrees.
Biological Data Science, MS
New College of Interdisciplinary Arts & Sciences
The Plan of study is the required curriculum to complete the program.
This degree follows the general graduate application deadlines.
This degree has graduate advising.
Pay for your graduate education
32 credit hours including the required applied project course (ACO 593, BIO 593 or MAT 593), or
32 credit hours and a thesis
Required Core (12 credit hours)
ACO 501 Database Systems and Problem Solving in Python (3)
BIO 614 Biometry (4)
LSC 519 Applied Learning Lab (1)
LSC 547 Wet Laboratory Experience (1)
STP 560 Experimental Statistics in Biology (3)
Other Requirements (9 credit hours)
LSC 555 Integrative Biology I (3)
LSC 556 Integrative Biology II (3)
LSC 562 Applied Mathematics Techniques in Biology (3)
Electives or Research (5 credit hours)
Culminating Experience (6 credit hours)
ACO 593 Applied Project (6)
BIO 593 Applied Project (6)
MAT 593 Applied Project (6)
ACO 599 Thesis (6)
BIO 599 Thesis (6)
MAT 599 Thesis (6)
Additional Curriculum Information
Other requirement, elective and research coursework may be substituted with approval of the academic unit. Students should see the academic unit for the approved electives and research course list.
Students choose one culminating experience option based on their emphasis area in biological data science.