DBS Computational Biology Certificate

Originally launched in 2018, the Computational Biology Certificate program is a recognition by the Biological Sciences department of the high demand for individuals who are trained in computational approaches that are now required for analyzing large biological data sets. While this includes the genomics data revolution, large data sets are now common in a variety of biological fields, including medicine, physiology, ecology, etc. The goal of the certificate is to provide training for graduate students so that they can become competitive for future positions in academia, government, and/or industry.

Specifically, our goal is that upon completion of the program, students will have the tools necessary to:

1. Exhibit proficiency in the comprehension, planning and implementation of computationally intensive experiments to identify patterns, trends, and associations in large biological-based data sets.
2. Convey analytical results, originating from varying data sources (e.g. next-generation DNA sequencing, high-throughput sensors) to other scientists as well as the general public in both written and oral formats.

The certificate consists of 18 credit hours of coursework. The first 12 hours are required and the last 6 are from a range of possible elective course work. It is suggested that students first enroll in Introduction to Computational Biology (BIOL 6800) which is offered in Fall semesters. This course provides students with a solid foundation in Linux and R. Intermediate coursework includes required courses in Statistics (STAT 7000) and Scripting (BIOL 7180). Elective coursework is very interdisciplinary and allows a lot of flexibility (see below). Any exceptions to these should be requested through the Graduate Coordinator of the Certificate Program Dr. Laurie Stevison. Students should plan to end their course work with the capstone colloquium course (BIOL 7800). This course is also taught in Fall semesters and includes traditional reading of the scientific literature as well as a final project to solidify the curriculum objectives.

How to enroll in the Certificate Program:

Interested students who are already enrolled in graduate school at Auburn need only to file a curriculum change form with the graduate school to ADD the Computational Biology Certificate (SM_GCRT_CBIO). This will enroll you in the certificate program. It is highly encouraged that this be done early in your time at Auburn. This form needs to be signed by Dr. Stevison and your current advisor.

Curriculum Change Form Links:

Domestic Students: https://gradforms.auburn.edu/CurriculumChangeDomestic.aspx

International Students: https://gradforms.auburn.edu/CurriculumChangeIntl.aspx

Fill out the form online and click continue. Then print the page that is loaded, and have your former major professor/advisor, proposed major professor/advisor, and graduate program officer sign it. You may either print out a physical copy or print to PDF and email the copy for signatures. Submit the signed and completed form to the Graduate School at Hargis Hall between 7:45 A.M. and 4:45 P.M., M-F or to your graduate advisor/GPO to send over electronically. It is very important to make sure you don’t “drop” your PhD/MS degree when you make this change. 

Earning the certificate:

When you have completed the requirements for the Certificate, submit your graduation application the term you take your final certificate course. You can do this AFTER the term when you take your final course, but not before.

Note, you must apply for graduation in the semester BEFORE you plan to graduate, so you cannot earn the certificate in the same semester you apply for graduation. Make sure to do this early! Because the certificate is not a degree granting program, you can graduate from the certificate BEFORE you plan to graduate from your primary degree program.

Below is the link to the AU Bulletin which describes what is needed to complete the computational biology certificate.

Auburn Bulletin - Computational Biology — Graduate Certificate 

Here is a link to FAQs regarding how the certificate is awarded and recognized: 

http://graduate.auburn.edu/prospective-students/graduate-certificate-programs/graduate-certificate-program-faqs/

Computational Biology Certificate Electives List (current as of 10/2023)

BIOL 6170 - Population Genetics

BIOL 6370 - Molecular Ecology

BIOL 6850 - Functional Genomics

BIOL 6860 - Bioinformatics

BIOL 7250 - Practical Data Analysis and Computation for the Life Sciences (Cross-listed as STAT 7250)

BIOL 7210 - Evolutionary Ecology

BSEN 6220 - Geospatial Technologies in Biosystems

CHEM 6450 - Foundations of R for DBER

COMP 7970 - Data Science Algorithms in Computational Biology

ENT 7230 – Practical Evolution

FISH 7350 - Meta-Analysis

FORY 6470 - GIS Applications in Natural Resources

FORY 6480 - GIS Database Design and Analysis

FORY 7250 - Advanced Ecosystem Modeling

FOWS 7150 - Spatial Statistics for Natural Resources

GEOG 6830 - Geographic Information Systems

PLPA 6820 – Principles and techniques of reproducible science (Cross-listed as ENTM/APBT 6820)

PLPA 7880 – Plant Microbial Ecology and Omics

STAT 6210 - R Programming for Data Science

STAT 7250 - Practical Data Analysis and Computation for the Life Sciences (Cross-listed as BIOL 7250)

WILD 7150 - Advanced Analysis for Ecological Sciences

WILD 7650 - Introduction to Bayesian Modeling in Natural Resources