Computational Life Sciences
Requirements
Description
In the life sciences, employers need graduates who are skilled in understanding and interpreting data. In particular, students who have experience using new, computational approaches and computer programs to process data are in demand. By completing this concentration in computational life sciences, students learn how to identify and interpret data that is generated from a wide range of fields in the life sciences. These fields include, but are not limited to: ecology, botany, evolutionary biology, neuroscience, molecular and cellular biology, and animal behavior. Students learn about many types of data generated from sources such as DNA, RNA, protein, imaging, conservation and even from long-term ecological research sites.
Students are introduced to a suite of computational approaches that are used to analyze, visualize and interpret this data. Finally, students will delve into the ethical implications of collecting, analyzing and sharing the results of computational life sciences data.
Requirements
- Students must complete a minimum of 15 credit hours including 12 of upper division courses in the life sciences and at least 6 upper division hours taken with the College of Liberal Arts and Sciences.
- The core consists of one computing course and one ethics course.
- A minimum of nine credit hours in elective courses complete the certificate.
- The computing course not used toward the core requirements may be used toward the elective credit hours.
- A grade of C (2.00 on a 4.00 scale) or higher is required for all courses used toward the concentration.
Required Courses -- 6 credit hours
BIO 316 History of Biology: Conflicts and Controversies (H) or BIO 317: History of Science (HU & H) or BIO 318: History of Medicine (HU & H) (3)
BIO 439 Computing for Research or BIO 440: Functional Genomics (3)
Electives -- 9 credit hours
BIO 355 Introduction to Computational Molecular Biology (CS) (3)
(Pre- or corequisite(s): BIO 340 or LSC 347 or MBB 347 with C or better)
BIO 411 Quantitative Methods in Conservation and Ecology (4)
BIO 439 Computing for Research (3)
BIO 494 Genomic Analysis (3)
BMI 311 Modeling Biomedical Knowledge (3)
BMI 312 Modeling Biomedical Data (3)
BMI 330 Topics in Translational Bioinformatics (3)
If not used as the required computing course, students may include BIO 439 or BIO 440 as a certificate elective.
YEAR
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LSC 426