4 Years On Campus Bachelors Program
The BS in Biological Sciences: Computational Biology (BCB) Track at the University of Rochester is ideal for students who enjoy both biology and technology and want to use computing to solve real biological problems. Students build a strong foundation in biology while developing skills in programming, mathematics, statistics, genomics, and data analysis, preparing them for opportunities in computational biology, bioinformatics, biotechnology, and related life-science fields.
Curriculum Structure
Year 1: Students start by building a solid foundation in biology and chemistry. Courses such as BIOL 110L: Principles of Biology I with Lab and BIOL 111L: Principles of Biology II with Lab introduce core biological concepts, while CHEM 131: Chemical Concepts I with Lab and CHEM 132: Chemical Concepts II with Lab provide the chemistry background needed for later coursework.
Year 2: Students move into genetics while continuing to develop the scientific and quantitative skills needed for computational biology. They study BIOL 198 & 198P: Principles of Genetics with Lab or BIOL 190 & 198P: Genetics: From Mendel to Molecules with Genetics Lab, along with CHEM 203/207: Organic Chemistry I with Lab, while beginning to connect biological concepts with mathematics, statistics, and programming.
Year 3: The focus becomes more strongly connected to computational methods and biological data. Students can take courses such as BIOL 253L: Computational Biology with Lab and BIOL 257L: Applied Genomics with Lab, supported by subjects such as STAT 190: Introduction to Statistical Methodology and CSC 171: Introduction to Computer Science or CSC 161: Introduction to Programming.
Year 4: In their final year, students can build more advanced computational and biological expertise through courses such as CSC 172: Data Structures and Algorithms, CSC 240: Data Mining, BIOL 219L: Genomics of Quantitative Traits with Lab, or DSCC 201: Tools for Data Science. They can also explore areas such as BIOL 202: Molecular Biology, BIOL 243: Eukaryotic Gene Regulation, BIOL 250: Biochemistry, and BIOL 267: Human Evolutionary Genetics, depending on their interests and academic plan.
Focus Areas
Computational biology, bioinformatics, biological data analysis, genomics, genetics, programming, computer science, statistics, data science, data mining, algorithms, quantitative biology, molecular biology, evolutionary genetics, biochemistry
Learning Outcomes
Students develop the ability to use computational, statistical, and quantitative approaches to investigate biological questions. They learn how to work with genomic and biological datasets, apply programming and data-analysis techniques, interpret research findings, connect computer science with biological problems, and communicate scientific results effectively.
Professional Alignment (Accreditation)
The BCB Track is an academic biological sciences degree with a strong computational focus rather than a professional degree leading to a specific licensed occupation. Its combination of biology, computer science, statistics, mathematics, genomics, and data analysis gives students a useful foundation for careers and further study in areas such as computational biology, bioinformatics, genomics, biotechnology, and biological data science.
Reputation (Employability Rankings)
The University of Rochester's BCB Track gives students the opportunity to combine biological sciences with computational and quantitative subjects while studying within a research-focused university environment. The official program information does not provide a specific QS, Guardian, or program-level employability ranking for the Computational Biology track, so no specific ranking is claimed.
The BS in Biological Sciences: Computational Biology (BCB) Track gives students the chance to turn classroom learning into practical skills by combining biology with programming, statistics, genomics, and data analysis. Students work with biological data, develop computational skills through computer-based laboratory courses, and can gain research experience with University of Rochester faculty across the River Campus and University of Rochester Medical Center. The program also encourages collaborative research experiences, including iGEM, where students work together on biological engineering projects.
Students can build practical experience through a range of hands-on courses, research opportunities, and collaborative projects:
Computational Biology with Lab: BIOL 253L: Computational Biology with Lab gives students practical experience applying computational approaches to biological questions and datasets.
Applied Genomics with Lab: BIOL 257L: Applied Genomics with Lab allows students to work with genomic information and develop practical skills in analyzing biological data.
Genomics of Quantitative Traits: BIOL 219L: Genomics of Quantitative Traits with Lab combines genomics with quantitative and computational approaches, helping students understand how biological data can be used to study complex traits.
Programming and Computer Science: Courses such as CSC 161: Introduction to Programming or CSC 171: Introduction to Computer Science help students develop programming foundations. More advanced options include CSC 172: Data Structures and Algorithms and CSC 240: Data Mining.
Data Analysis using R: BIOL 218P: Data Analysis in R Computer Laboratory gives students practical experience using R for biological data analysis and statistical work.
iGEM collaborative project: Through BIOL 228A&B: iGEM I & II, students can work as part of a collaborative team to design and develop an engineered biological system using DNA technologies. The experience combines laboratory research, computational thinking, teamwork, project planning, and scientific communication.
Independent research: Students can undertake independent research with University of Rochester faculty at the River Campus or University of Rochester Medical Center. Depending on the project, students may gain experience with laboratory experiments, computational research, biological data analysis, and scientific reporting.
Faculty research mentorship: Students can connect with faculty members whose research interests match their goals and gain experience working under faculty guidance. The Biology Department also connects students with the University's Office of Undergraduate Research for additional research opportunities and support.
Beckman Scholars Program: Eligible students can apply for the Beckman Scholars Program, which provides selected students with a 15-month mentored research experience and $21,000 in research support.
Research environment: Students benefit from the University's research connections between the River Campus and University of Rochester Medical Center, giving them opportunities to engage with research across biology and biomedical sciences.
Computational and quantitative training: The BCB curriculum brings together programming, statistics, data mining, genomics, and computational biology, helping students develop the quantitative skills needed to work with modern biological datasets.
Additional laboratory opportunities: Depending on their academic plan, students may also explore research-focused courses such as BCH 308: Biochemical and Molecular Biology Techniques, BIOL 268: Lab in Molecular, Cell, and Developmental Biology, and NSCI 202: Experimental Design and Data Analysis.
The BS in Biological Sciences: Computational Biology (BCB) Track prepares students for careers that bring together biology, computer science, statistics, genomics, and data analysis. It can open doors to roles such as computational biology researcher, bioinformatics analyst, biological data scientist, and genomics research assistant, while also giving students a strong foundation for further study in research and related professional fields.
Students can strengthen their career preparation through Rochester's career services, research opportunities, and connections across its scientific community:
Career and employment support: The University's Greene Center for Career Education and Connections helps students with résumé development, interview preparation, career guidance, networking, and employment opportunities. Biology students can also explore undergraduate positions through JobLink, including opportunities within the Biology Department.
Research experience: Students can take part in independent research for academic credit with University of Rochester faculty on the River Campus or at the University of Rochester Medical Center. Depending on the project, students may gain experience with laboratory or computational research, biological data analysis, scientific reporting, and poster presentations.
Professional skill development: The SPARC pathway helps students develop professional, technical, and communication skills that can be valuable when entering research environments or preparing for employment and further study.
Employment outcomes: The University of Rochester's School of Arts & Sciences reports a 96% positive career outcome, with 53.5% of graduates entering the workforce and 42.7% continuing their education. The reported average first-destination salary is $65,827. These figures are for the School of Arts & Sciences overall and are not specific to the BCB Track.
Research environment: Students benefit from Rochester's research community, with opportunities connected to both the River Campus and University of Rochester Medical Center. Biology research covers areas including genetics, genomics, molecular biology, and computational biology, giving students exposure to a broad range of scientific work.
Collaborative opportunities: Students can participate in research-focused activities such as iGEM, where they work as part of a team on biological engineering projects. The Society of Undergraduate Biology Students also provides opportunities for networking, study groups, and research-shadowing experiences.
Graduation and research achievements: Students interested in demonstrating advanced research experience can pursue Honors in Research, which involves completing and defending a senior thesis. This can be particularly useful for students planning to apply for research positions, graduate programs, or other advanced academic opportunities.
Long-term professional value: The BCB Track is an academic biological sciences degree rather than a professional qualification linked to a specific licensed occupation. Its combination of biology, programming, statistics, genomics, and computational methods provides a strong foundation for long-term development in computational biology, bioinformatics, biotechnology, genomics, and biological data science.
Further Academic Progression:
After completing the BCB Track, students can continue their education through advanced programs such as the University of Rochester's MS or PhD programs in Biology. These programs allow students to build on their undergraduate knowledge and research experience while developing deeper expertise through advanced coursework and independent research.
The degree can also prepare students for medical, health-profession, biotechnology, bioinformatics, computational biology, and other graduate programs, depending on their academic and career goals. Because the BCB curriculum combines biological sciences with computer science, statistics, mathematics, genomics, and research, students have flexibility when choosing their next academic or professional step.


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