Independent Studies in Computational Biology

Introducing High School Students to Computational Biology

Independent Studies in Computational Biology (ISCB) immerses talented science and math students in systems genetics research. The course integrates genetics, statistical analysis, and the R programming language to bring a highly interdisciplinary research experience to students. Independent Studies in Computational Biology offers graduate level research experiences to high school students in order to accelerate their research careers at a very early age. Participating schools include the Maine School of Science and Mathematics, the North Carolina School of Science and Mathematics, and the Rockdale Magnet School of Science and Technology.

“I’m graduating in Quantitative Biology at UNC in ‘13 because of this class!” Justin Huang, Undergraduate Student, University of North Carolina

"I anticipated the ISCB course would have a great impact on our students, but could not have known how much the experience would influence me as a teacher, reigniting a drive and desire to ask questions and explore.” Deborah McGann, Chemistry Instructor, Maine School of Science and Mathematics

"This program presents students with the chance to do very advanced, very cutting-edge, very real-world science. These kids will leave here, go to good universities, and most will move seamlessly and effortlessly into research labs as freshmen." Bob Gotwals, Chemistry Instructor, North Carolina School of Science and Mathematics

AimsAims and Objectives

Students gain the experimental and computational knowledge necessary to embrace a systems biology approach, and experience authentic systems genetics research by designing and conducting independent research projects with guidance from Center faculty, staff and postdoctoral associates. [ More information ]


This two semester course trains students in core research competencies such as reading scientific literature, writing literature reviews and research proposals, and delivering oral presentations. Instruction includes research design and methods as well as skills in R programming and quantitative trait locus analysis. Students write an NIH-style research proposal in the first semester, and carry out research in the second semester using Center-generated data and tools. [ More information ]

ReadingRecommended Reading

Course reading includes current primary research articles and reviews from top tier journals including Nature and Science. Texts for background material in mouse genetics, quantitative trait locus analysis, and R programming are made available to each school as well. [ More information ]

PublicationsPublications by ISCB Students

Several students have published their research in scientific journals. [ More information ]