BS in Computational Biology

4 Years On Campus Bachelors Program

Florida State University

Program Overview

Florida State University’s BS in Computational Biology is an interdisciplinary program combining biological science, computer science, scientific computing, mathematics, statistics, and chemistry to prepare students to analyze complex biological data and develop biologically meaningful computational models. Student fit: It suits students interested in biology and bioinformatics who want to apply computational and quantitative tools to practical biomedical and biological problems, including areas such as genomics, systems biology, proteomics, metabolomics, ecology, and phylogeny.

Curriculum Structure

Year 1: Students establish their scientific and quantitative foundation through ENC1101, MAC1140, MAC1114, and CHM1045/CHM1045L in the first term, followed by MAC2311, CHM1046/CHM1046L, and ENC2135. The summer sequence adds PHY2048C and MAC2312, preparing students for the more specialized biology and computing coursework ahead.

Year 2: Students begin integrating biological science with scientific computing through BSC2010/BSC2010L, ISC3313 Introduction to Scientific Computing, BSC2011, and ISC3322. MAD2104 Discrete Mathematics I and ISC4221 further develop the mathematical and computational foundation needed for biological data analysis.

Year 3: The curriculum moves into core computational biology concepts with STA2171 Statistics for Biology, ISC4304 Programming for Scientific Applications, PCB3063 Genetics, and PCB4674 Evolution. Students also begin selecting biological electives, allowing them to develop knowledge in areas aligned with their interests.

Year 4: Students advance into upper-level computational and research-oriented study through ISC4220/ISC4221 Algorithms for Scientific Applications, BSC4933 Selected Topics in Biological Science, and ISC4934 or a Computer Science elective. The final year also provides an opportunity to bring biological and computational skills together through advanced study and the program's research-focused Computational Biology Practicum.

Focus areas: Computational biology, bioinformatics, biological data analysis, genomics, systems biology, imaging, proteomics, metabolomics, ecology, phylogeny, scientific computing, programming, genetics, and evolution.

Learning outcomes: Students develop the ability to understand biologically meaningful computational models, combine biological and quantitative skills, analyze large biological datasets, and apply computational approaches to practical biomedical problems.

Professional alignment (accreditation): The BS in Computational Biology is an interdisciplinary degree offered through FSU's Biological Science and Computer Science departments; ABET accreditation does not apply to the Computational Biology degree, as FSU specifically states that ABET accreditation applies to its BS in Computer Science.

Reputation (employability rankings): QS World University Rankings 2027: Florida State University is ranked #=546 globally; QS's institutional ranking is not a specific ranking of the Computational Biology program.

Experiential Learning (Research, Projects, Internships etc.)

Florida State University’s BS in Computational Biology is built around applying computation to real biological problems, combining biology, computer science, scientific computing, statistics, and mathematics. The Biology Track goes beyond classroom study through a required Research Practicum in Computational Biology, where students spend at least two semesters conducting research under faculty guidance, maintain weekly research reports, produce a written project, and defend their work orally before a faculty committee.

Students can develop practical computational and research skills through these opportunities:

Research Practicum: Students complete a faculty-supervised research project for at least two semesters, culminating in a written report and oral defense before a committee.
Programming skills: The curriculum includes ISC 4304C Programming for Scientific Applications, alongside ISC 3222 Symbolic and Numerical Computations and ISC 3313 Introduction to Scientific Computing, providing direct preparation for computational biological analysis.
Algorithms and scientific computing: Students study Algorithms for Scientific Applications I and II, developing computational approaches applicable to biological datasets and biomedical problems.
Python and R: FSU's computational biology research projects specifically identify Python and R as tools students may use for genomic-data analysis, including projects involving complex behavior and gene-expression research.
High-performance computing: Students can engage with research involving high-performance computational biology, including next-generation sequencing analysis, metagenomics, and computational mass fingerprinting.
Molecular simulation: Research opportunities include computer simulation of biomolecules, where students apply molecular-dynamics simulation methods to problems involving biomolecular recognition, protein dynamics, and drug discovery.
Genomics research: Students can participate in projects involving genomic and epigenomic data analysis in maize, as well as computational studies of genomic datasets related to biological behavior.
Cryo-EM and biological imaging: FSU research opportunities include high-resolution cryogenic electron microscopy, with projects requiring skills in Linux, Python, or web-based software development.
Computing facilities: FSU Biology provides computational resources including the Pauper and Vespula computing clusters and dedicated computer labs, supporting computational research and data-intensive work.
Research laboratories: Biology facilities include DNA Sequencing, Molecular Cloning, NGS Library, Analytical, and Biological Science Imaging facilities, giving students access to a broader research environment surrounding computational biology.
NGS equipment: The NGS Library Facility includes equipment such as the Covaris ME220, Bioanalyzer 2100, and Pippin HT Size Selection system for next-generation sequencing library construction and quality control.
Internships and research: FSU's Career Center specifically lists the Center for Bioinformatics and Computational Biology, Computational Biology Summer Program, Bioinformatics Internship, Center for Genomics and Personalized Medicine, Undergraduate Research Opportunity Program, and Directed Individual Study as relevant experience opportunities.
Scientific research experience: FSU Biology faculty welcome undergraduates into their laboratories, with opportunities to publish scientific papers and present at scientific meetings.
Industry-oriented experience: FSU's Career Center identifies relevant sample employers including Health Diagnostic Laboratory, Inc., HCA Florida Capital Hospital, Apple, Lockheed Martin, and Raytheon, alongside research/development, biotechnology, pharmaceutical, and software work settings.

Progression & Future Opportunities

The BS in Computational Biology at Florida State University combines biological science with computation, data analysis, and quantitative methods, preparing graduates for work across biotechnology, biomedical research, healthcare, and data-focused life-science organizations. The degree also provides a strong foundation for graduate and professional study in computational biology, bioinformatics, biology, biomedical sciences, and related fields.

Career roles: Bioinformatics Analyst, Computational Biologist, Biological Data Analyst, Research Associate:

Career support: The FSU Career Center helps students prepare for employment through career advising, resume and cover-letter assistance, interview preparation, career fairs, employer events, internships, and job-search resources.
Employment outcomes: FSU publishes career-outcome information through its First Destination Survey and Career Center resources. Program-specific salary figures for Computational Biology graduates are not stated on the official FSU program pages, so no program-specific salary figure is provided here.
Industry connections: FSU's Institute of Molecular Biophysics brings together biology, chemistry, physics, mathematics, and computer science and supports research involving computational and quantitative approaches to biological problems. The university also provides students with opportunities to engage with faculty research and interdisciplinary scientific work.
Research opportunities: Students can gain experience through undergraduate research with FSU faculty, developing skills applicable to computational biology, bioinformatics, molecular biology, and quantitative biological research.
Accreditation value: Florida State University is accredited by the Southern Association of Colleges and Schools Commission on Colleges (SACSCOC) to award bachelor's, master's, and doctoral degrees. This institutional accreditation provides long-term academic recognition for the degree.
Graduation outcomes: FSU's career-outcome resources track graduates' employment, continuing education, and other post-graduation destinations, helping students understand pathways after completing their undergraduate studies.

Further Academic Progression: Graduates can continue into master's or doctoral study in computational biology, bioinformatics, biological sciences, biomedical sciences, molecular biology, data science, or related disciplines. The quantitative and biological foundation can also support progression into research-oriented graduate programs and other professional pathways where biological data analysis is important.