Graduate Certificate in Bioinformatics
This certificate program will provide bioinformatics training for students from diverse backgrounds with interests in applications of mathematics and computer programming in biology. With an interdisciplinary approach, students will be introduced to the use of computational skills, mathematical modeling, and computing techniques to study biology relevant to basic and biomedical sciences in agricultural, environmental, or health-related areas. The training is appropriate for those who have taken introductory courses in biology, mathematics, and computer programming during their undergraduate studies.
Admission Requirements
Admission to the program requires admission to the Graduate School. Prerequisites to admission include Molecular Cell Biology (BIOL 3314), Elementary Data Structures (CS 2401), and Elementary Statistical Methods (STAT 2480), or equivalents, with a minimum grade of "B" in each course.
Degree Plan
This certificate program requires completion of 15 credit hours of courses: Bioinformatics I (BINF 5351), Bioinformatics II (BINF 5352), plus 6 credit hours of elective courses from a prescribed list, and a 3-credit hours free elective course approved by the graduate advisor.
| Code | Title | Hours |
|---|---|---|
| Required: | ||
| BINF 5351 | Intro. Bioinformatics I | 3 |
| BINF 5352 | Intro. Bioinformatics II | 3 |
| List of Prescribed Elective Courses | ||
| Select six hours from the following: | 6 | |
| Biology Seminar/Bioinformatics | ||
| Chem. Sem. for Bioinformatics | ||
| CS Seminar for Bioinformatics | ||
| Math Sem. for Bioinformatics | ||
| Anal./Model of Bio Structures | ||
| Post-Genomic Analysis | ||
| Biosystematics | ||
| Advances Immunological Concept | ||
| Physiology of Bacterial Cell | ||
| Structure/Funct Macromolecules | ||
| Molecular Pathogenesis | ||
| Contem Topics Organic Chemistr | ||
| Contemp Topics in Biochemistry | ||
| Database Systems | ||
| Advanced Computer Architecture | ||
| Advanced Algorithms | ||
| Interval Computations | ||
| Comp Methods of Linear Algebra | ||
| Techniques in Optimization | ||
| Statistical Programming | ||
| Categorical Data Analysis | ||
| Stochastic Processes | ||
| Multivariate Data Analysis | ||
| Time Series Analysis | ||
| Statistical Computing | ||
| Intro to Statistical Analysis | ||
| Free Elective | ||
| Select a three hour free elective course approved by graduate advisor | 3 | |
| Total Hours | 15 | |