Canisius University

What you'll study

This interdisciplinary major combines core coursework from biology, mathematics and computer science to give students a working knowledge of molecular biology and the quantitative tools used to analyse biological systems. You will study foundational subjects such as calculus, linear algebra and statistics alongside programming, algorithms and software development. Biological courses cover cellular and molecular biology, genetics and genomics, laboratory techniques and molecular evolution.

Typical modules and topics include:

• Mathematics: calculus sequence, linear algebra, differential equations, probability and mathematical statistics, numerical methods and modelling.
• Computer Science: introductory programming (commonly Python or Java), data structures and algorithms, databases, scientific computing, and machine learning or data-mining electives.
• Biology: general biology, molecular and cellular biology, genetics, genomics and bioinformatics-focused laboratory courses.
• Integrated/Applied Courses: statistical methods for biological data, computational genomics, systems biology, sequence analysis, structural bioinformatics and applied modelling of biological systems.
• Capstone and Research: a senior capstone project, practicum or independent research placement supervised by faculty, emphasising application of computational tools to real biological datasets.

The programme emphasises hands-on experience with common bioinformatics tools and programming languages, data analysis workflows, reproducible research practices and presentation of scientific results.

Entry requirements

Entry to the bachelor programme typically requires a high school diploma or equivalent with a strong background in mathematics and science. Successful applicants usually have completed courses in algebra, precalculus or calculus, chemistry and biology. Prior exposure to programming is advantageous but not always mandatory; introductory modules are provided for students new to computer science.

Admissions decisions are made holistically and may take into account academic transcripts, letters of recommendation, a personal statement and any relevant extracurricular or research experience. Applicants who transfer from other institutions should provide college transcripts and, where applicable, descriptions of completed coursework for credit evaluation. Placement testing or bridging modules can be available if you need to strengthen preparation in mathematics, programming or laboratory skills.

Career prospects

Graduates are prepared for roles that require quantitative analysis of biological data and the development of computational solutions to life-science problems. Common career paths include:

• Bioinformatics analyst or specialist in academic, clinical or industry laboratories
• Computational biologist or data scientist in biotechnology and pharmaceutical companies
• Research assistant in genomics, proteomics or systems biology labs
• Software developer for scientific tools, databases or laboratory information systems
• Clinical data analyst or roles in public health analytics

Many graduates also pursue graduate study—master's or PhD programmes in bioinformatics, computational biology, biostatistics, systems biology or related fields—or professional degrees in medicine and allied health, leveraging the programme’s quantitative and laboratory foundations.

Why study at Canisius University

Canisius offers a small, student-centred liberal arts environment where interdisciplinary programmes are supported by close faculty mentoring and accessible research opportunities. Students benefit from small class sizes that allow personalised instruction across the departments contributing to this major, including biology, mathematics and computer science.

The university’s location provides access to regional hospitals, research institutions and biotech employers for internships and collaborative projects, and the curriculum emphasises experiential learning through laboratory courses, internships and a senior capstone. Academic advising and career services support students in planning coursework, securing research placements and preparing for graduate study or employment in computational life sciences.