Computational Biology

Description

Computational biology involves the analysis and discovery of biological phenomena using computational tools, and the algorithmic design and analysis of such tools. The field is widely defined and includes foundations in computer science, applied mathematics, statistics, biochemistry, molecular biology, genetics, ecology, evolution, anatomy, neuroscience and visualization. The program educates the student liberally in these fields, building on a foundation of coursework that may then focus via several possible tracks. The program offers four tracks: computational genomics, biological sciences, molecular modeling and applied mathematics and statistical genomics. The program requires a senior capstone experience that pairs students and faculty in creative research collaborations. 

Student Goals

Students in this concentration will:

• Develop a broad foundation in biological sciences, applied mathematics, and statistics
• Understand the history and evolution of the study of the human genome
• Acquire advanced computational skills
• Learn how to formulate a scientific question related to statistical genomics
• Collaborate with a faculty member on a research-based senior capstone experience

Requirements

Click here for a list of the Computational Biology concentration requirements. For more information about this concentration, please visit the department's website.

Honors and Capstones

Students complete a research project in their senior year under faculty supervision. The themes of such projects evolve with the field and the technology, but should represent a synthesis of the various specialties of the program. A minimum of one semester of independent study is required (such as BIOL 1950 or CSCI 1970), although many students may conduct a full year of independent study. To be a candidate for Honors, a student must have a course record judged to be excellent by the concentration advisor and must complete a thesis judged to be outstanding by the faculty member supervising the work. Please see the department's website for a complete description of program requirements.

Tracks

• Applied Mathematics and Statistical Genomics
• Biological Sciences
• Computational Genomics
• Molecular Modeling

Liberal Learning

This concentration allows you to address the following Liberal Learning goals:

• Collaborate fully
• Engage with your community
• Develop a facility with symbolic languages
• Experience scientific inquiry

Download the full statement on Liberal Learning at Brown

Back to Focal Point

Affiliated Departments

• Center for Computational Molecular Biology
• Departments in the Program in Biology

Advisors

• Sorin Istrail
• Charles Lawrence
• David Rand
• Benjamin Raphael
• J. William Suggs

Graduating Class

Alumni Pathways

Alumni with degrees in Computational Biology have gone on to careers in management consulting, Bioinformatics and Quantitative Biology research, medicine, and in health technology fields.

Dept. Undergraduate Group

Student Leaders:

• Milan Kantesaria