The recent explosion of high-throughput experimental techniques (e.g., next-generation sequencing, proteomics, metabolomics, imaging, etc.), coupled with rapid advances in computational and statistical technologies, has laid the foundation for the emergence of a highly interdisciplinary field of bioinformatics. This undergraduate degree program in Bioinformatics is strategically designed with core courses in statistics/mathematics, biology/genetics, and computer science, as well as comprehensive and advanced training in bioinformatics. The Bioinformatics curriculum focuses on cultivating students with knowledge and expertise in biology, statistics, computer science, and, most importantly, the seamless integration of these diverse domains. The overall purpose of this program is to empower graduates with a profound grasp of biological, genetic, and genomic principles, complemented by robust skills in statistics, computation, and data science. This program aims to nurture the next generation of bioinformaticians, computational biologists, data scientists, and researchers in various life science, biotechnology, and healthcare settings. This program will structurally and administratively reside in the Department of Statistics, in close partnership with the Department of Biology and with full support from the Department of Computer Science and Engineering. Students will be required to successfully complete a minimum of 120 credit hours in order to earn their degree.
Learning outcomes
- Mastery of principles and concepts of biology, computer science, and statistics. Bioinformatics students will demonstrate mastery of principles and core concepts of biology, computer science, and statistics, thereby exhibiting proficiency and competence in the highly interdisciplinary field of bioinformatics.
- Data analytics and computation. Bioinformatics students will demonstrate ability to analyze large high-throughput omics data, implement statistical methods, execute existing programs and software, and document and debug code in programming languages including both R and Python.
- Knowledge of genomic technologies and bioinformatic methods. Bioinformatics students will develop problem-solving and communication skills to comprehend experimental techniques, analyze high-throughput data, and effectively dissimilate results and methodologies in written and oral formats.
Questions?
Email Dr. Yuchao Jiang (yuchaojiang@tamu.edu) and Courtney Shuttlesworth (cshuttles@tamu.edu).