Bioinformatics and computational biology incorporate computer science, statistics, and information technology to create tools for processing and analyzing biological data, and to advance the understanding of living systems through computation.
At Illinois Tech the bioinformatics major blends courses in biology, chemistry, and physics with courses in programming, statistics, and other methods, producing graduates who are both strong in science and able to develop and use data processing tools to advance scientific knowledge.
Our program is scientifically rigorous, providing students with in-demand programming and analytical skills through a solid, balanced offering in STEM courses. Combined with undergraduate research opportunities, this rounded curriculum provides the knowledge, skills, and experiences to pursue careers in bioinformatics or computational biology.
Courses include programming in Perl, C++, and Java; data structure and algorithms; data mining; statistics; human biology; genetics; genomics and transcriptomics; and more.
Two tracks are available. Applied Bioinformatics has more required and elective courses in computer science. Computational Biology has more required and elective courses in biology.
Bioinformatics blends courses in biology, chemistry, and physics with programming, statistics, and other methods, producing graduates with strong computational and scientific skills. Two tracks include Applied Bioinformatics, with more courses in computer science, and Computational Biology, with more courses in biology.
Most bioinformatics positions require an advanced degree. The Illinois Tech major helps prepare you for graduate school, as well as entry-level, technical positions.
- Computational biologist
- Data scientist
Disclaimer for prospective students, please read.
Admission to Illinois Tech is required to enroll in the B.S. bioinformatics program. Consult your academic adviser before transferring into the program.
Not what you're looking for? View all of Illinois Tech's programs in artificial intelligence, machine learning, computation, and data science.