A 12-Credit, 100% Online Graduate Program Teaching Practical Skills in Bioinformatics and Genomic Data Analysis
Developed and taught by the faculty at UConn's Computational Biology Core in the Institute of Systems Genomics, the Genomic Data Analysis Online Graduate Certificate program provides an exceptional opportunity for students to gain specialized training in bioinformatics and computational biology without committing to a multi-year full-time graduate degree. The 100% online graduate certificate can be completed in one year.
Meet the Growing Demand for Bioinformatics Data Skills
As the field of genetics and genomics continues to grow rapidly, the demand for individuals who can rigorously and reproducibly extract insight from large 'omic datasets is on the rise. UConn’s Genomic Analysis Certificate is designed to equip students with the practical skills and theoretical knowledge to accomplish this. The curriculum consists of four highly interactive, UConn faculty-led online courses introducing students to key concepts in the analysis of genomic data, and provides extensive hands-on experience analyzing high-throughput sequencing data on the UConn Health Center's high performance computing cluster.
Learn to Analyze Genomic Data Rigorously and Reproducibly
Upon completion of the program, students will have the skills to:
- Navigate command line-driven high performance computing infrastructure essential to cutting edge computational biology.
- Execute and interpret common computational workflows in genomics using Linux, R and python-based tools.
- Make those workflows rigorous, reproducible, and portable using Nextflow, git and software containers.
- Communicate results quickly and effectively with text and figures.
Note: We are currently accepting applications for the Fall 2024 semester. Please apply early to avoid last minute delays.
Noah Reid is an Assistant Research Professor in the Institute for Systems Genomics at the University of Connecticut. He received his PhD in Ecology and Evolutionary Biology from Louisiana State University. His research interests include evolutionary genomics, bioinformatics, and computational biology. Dr. Reid has published numerous research articles in leading scientific journals, and is dedicated to mentoring and teaching students in the field of genomics. He is the Program Director and lead faculty member for UConn’s Genomic Data Analysis Online Graduate Certificate Program.
Jill Wegrzyn is an Associate Professor in the Department of Ecology and Evolution and Faculty Director of the Computational Biology Core at the University of Connecticut. She received her Ph.D. in Information Systems and Technology at the University of California, San Diego. Dr. Wegrzyn's research focuses on understanding the genetic basis of complex traits in forest trees and developing genomic tools for their improvement. She has published numerous research articles in peer-reviewed journals and has received multiple grants to support her research. Further, Dr. Wegrzyn is actively involved in teaching and mentoring students in genomics and bioinformatics, and advises multiple graduate students and postdoctoral researchers. Her expertise in genomics data analysis and her passion for teaching make her a pivotal member of the faculty within the Genomics Data Analysis Online Graduate Certificate program.
Vijender Singh is an accomplished bioinformatician with extensive experience in genomic data analysis and currently sits as the Associate Director of UConn’s Computational Biology Core. He earned his PhD the Indian Institute of Science and as a Bioinformatics Scientist, often works closely with private medical laboratories as a consultant. Dr. Singh has authored numerous publications in high-impact journals and has presented his research at many national and international conferences. His areas of expertise include genomic data analysis, statistical analysis, and algorithm development. As an instructor in UConn's Genomics Data Analysis Online Graduate Certificate program, Dr. Singh brings his knowledge and experience to help students develop the skills needed to excel in the rapidly growing field of genomics.
Students taking courses in the Genomic Analysis Online Graduate Certificate pay a comprehensive fee of $925 per credit or $2,775 for a 3-credit course. The cost of the 12-credit certificate program is $11,100.
Graduate students who are enrolled in a non-approved graduate certificate program (only) are not eligible to receive federal financial aid (Federal Stafford Loan and Graduate PLUS Loan funds).
Students enrolled in the Genomic Analysis Online Graduate Certificate program may wish to consider:
- UConn’s payment plan: https://bursar.uconn.edu/paymentplans/.
- Alternative (Private) Loan financing: http://financialaid.uconn.edu/gradalt/.
- Checking with employers for tuition reimbursement opportunities.
Are you currently a UConn student in a master’s degree program?
- Graduate students who are seeking a graduate degree and are simultaneously enrolled in the Genomic Analysis Online Graduate Certificate program are eligible to apply for federal financial aid.
Information on the financial aid application process for Graduate Students is available here: http://financialaid.uconn.edu/graduate/
Please visit https://bursar.uconn.edu/tuitionandfees/ to learn more about Graduate Student fees at UConn.
ISG 5301 - Basic Concepts in Genomic Data Analysis I (2-credit) (semester)
This course will cover fundamental concepts in genomics and the analysis of genomic data. Course content will provide an overview of the types of questions that can be addressed with genomic data, sequencing technologies used to collect those data, computational tools and infrastructure used to analyze them, the basics of bioinformatic workflows, and the interpretation and communication of high dimensional data through text and figures.
ISG 5302 - Basic Concepts in Genomic Data Analysis II (2-credit) (semester)
This course will cover in depth the concepts underlying several key genomic workflows, including assembly, annotation, variant detection and count-based functional genomic approaches. It will also cover retrieving and depositing data in several common public databases. It will introduce higher level computational tools used in version control and pipeline development, and the communication of results in public presentations.
ISG 5311 - Genomic Data Analysis in Practice I (4-credit) (semester)
This course will introduce students to key tools used in genomic data analysis in academic and industrial settings. Students will become familiar with the Linux operating system, learn to write scripts in the bash language, and learn how to interact with and operate a high performance computer cluster (HPC) through the job scheduler SLURM. Students will be introduced to the statistical computing language R and the tidyverse package for data manipulation. The course will also cover approaches for data and project management. The course will use RNA-seq as a model workflow to introduce tools and concepts.
ISG 5312 - Genomic in Data Analysis II (4-credit) (semester)
This course will introduce students to several key genomic data analysis workflows. It will build on skills developed in the previous semester by walking students through tools used to accomplish these workflows. It will also introduce higher level bioinformatics tools used to ensure reproducibility and re-usability of code, including version control and pipeline development tools. It will familiarize students with searching, accessing and depositing data in commonly used public databases. Students will develop skills in oral presentation of scientific results.
How to Apply & Begin Your Application
To apply for admission to the Genomic Data Analysis Online Graduate Certificate, complete the application process which begins at the link below. Applicants must have completed a Baccalaureate degree or higher from a regionally accredited college or university.
This program only accepts students within the fall semester.
The GRE, GMAT, and Residence Affidavit are not required.
Within the application, please select the following when applying:
- Levels of Study: Certificate
- Academic Areas: Health
- Program: Genomic Data Analysis Grad Cert
- Campus: Online
Applications are evaluated as soon as the student’s file is complete.
If you have any questions on how to use the online application system, please contact The UConn Graduate School at 860-486-3617.
International Students: This program is a part-time and online program. Pursuant to U.S. immigration regulations, the University of Connecticut may not sponsor F-1 and J-1 visas for the purpose of coming to the U.S. for enrollment in this program. International students may enroll in this program if they are currently in the U.S. in another visa status that permits foreign nationals to engage in school enrollment while meeting their primary visa objective, or if they complete the program from their home country.
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Genomic Data Analysis Online Graduate Certificate Program Information Sessions
Attending an information session on UConn's Genomic Data Analysis Online Graduate Certificate program can provide valuable insight into the program and its curriculum.
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Program Manager & Research Assistant Professor
Department of Molecular and Cell Biology
University of Connecticut
An Online Graduate Program from a Top-Ranked (R1) University
The University of Connecticut is ranked in the Top 25 Public Schools by US News & World Report and is accredited by the New England Association of Schools and Colleges.