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.
Students may pursue a Bachelor of Arts or a Bachelor of Science. Students pursuing the ScB have the option of electing a concentration in Computational Biology with one of three focus areas: Computer Sciences, Biological Sciences, or Applied Mathematics & Statistics. Both programs require a senior capstone experience that pairs students and faculty in creative research collaborations.
Standard program for the A.B. degree
| Prerequisites: | 2 | |
| Single Variable Calculus, Part II | ||
or MATH 0170 | Single Variable Calculus, Part II (Accelerated) | |
| The Foundation of Living Systems | ||
| General Core Requirements: Biology | 2 | |
| Genetics | ||
| Biochemistry | ||
or BIOL 0500 | Cell and Molecular Biology | |
| General Core Requirements: Chemistry | 1 | |
| Equilibrium, Rate, and Structure | ||
or CHEM 0350 | Organic Chemistry I | |
| General Core Requirements: Computer Science | 2 | |
| Computing Foundations: Data and Computing Foundations: Program Organization and Program Design with Data Structures and Algorithms | ||
OR | ||
| Program Design with Data Structures and Algorithms and Introduction to Object-Oriented Programming and Computer Science and Computer Science: An Integrated Introduction | ||
OR | ||
| Accelerated Introduction to Computer Science and Program Design with Data Structures and Algorithms and Introduction to Software Engineering and Introduction to Computer Systems and Theory of Computation | ||
| General Core Requirements: Probability & Statistics | 1 | |
| Statistical Inference I | ||
OR | ||
| Advanced Introduction to Probability for Computing and Data Science | ||
OR | ||
| Probability | ||
| Comp Bio Core Course Requirements | 4 | |
| Computational Molecular Biology | ||
| Inference in Genomics and Molecular Biology | ||
AND two of the following: | ||
| Algorithmic Foundations of Computational Biology | ||
| Deep Learning | ||
| Foundations of Population Genetics | ||
| Computational Methods for Studying Demographic History with Molecular Data | ||
| Human Population Genomics | ||
| Methods in Informatics and Data Science for Health | ||
| Machine Learning | ||
| Computational Probability and Statistics | ||
| Statistical Inference II | ||
Additional course with Director approval | ||
| Total Credits | 12 | |
University Writing Requirement:
As part of Brown’s writing requirement, all students must demonstrate that they have worked on their writing both in their general studies and their concentration. There are a number of ways for Computational Biology concentrators to fulfill these requirements:
- Enrolling in an independent study: CSCI 1970, BIOL 1950, APMA 1970
- Writing an Honors Thesis
- Taking a “WRIT” course in the final two years
Capstone Experience
Students enrolled in the computational biology concentration will 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. The requirements are either one semester of reading and research with a CCMB Faculty member or approved advisor, or a 2000-level Computational Biology course.
Standard program for the Sc.B. degree
| Prerequisites | ||
| MATH 0100 | Single Variable Calculus, Part II (or equivalent) | 1 |
| or MATH 0170 | Single Variable Calculus, Part II (Accelerated) | |
| BIOL 0200 | The Foundation of Living Systems (or equivalent) | 1 |
| General Core Course Requirements: Biology | ||
| BIOL 0470 | Genetics (prerequisite BIOL 0200 or equivalent) | 1 |
| BIOL 0280 | Biochemistry | 1 |
| or BIOL 0500 | Cell and Molecular Biology | |
| General Core Requirements: Chemisty | ||
| CHEM 0330 | Equilibrium, Rate, and Structure | 1 |
| or CHEM 0350 | Organic Chemistry I | |
| General Core Requirements: Computer Science | 2-4 | |
| Computing Foundations: Data and Computing Foundations: Program Organization and Program Design with Data Structures and Algorithms | ||
| OR | ||
| Program Design with Data Structures and Algorithms and Introduction to Object-Oriented Programming and Computer Science and Computer Science: An Integrated Introduction | ||
| OR | ||
| Accelerated Introduction to Computer Science and Program Design with Data Structures and Algorithms and Introduction to Software Engineering and Introduction to Computer Systems and Theory of Computation | ||
| CSCI 0220 | Introduction to Discrete Structures and Probability | 1 |
| General Core Requirements: Probability & Statistics | ||
| APMA 1650 | Statistical Inference I | 1 |
| or CSCI 1450 | Advanced Introduction to Probability for Computing and Data Science | |
| or MATH 1610 | Probability | |
| General Core Requirements: Computational Biology | ||
| CSCI 1810 | Computational Molecular Biology | 1 |
| APMA 1080 | Inference in Genomics and Molecular Biology | 1 |
| Capstone Experience | 1 | |
| Directed Research/Independent Study | ||
| Individual Independent Study | ||
| Six courses in one of the following three tracks: | 6 | |
| Computer Science Track: | ||
Three of the following: | ||
| Introduction to Computer Graphics | ||
| Database Management Systems | ||
| Artificial Intelligence | ||
| Machine Learning | ||
| Deep Learning | ||
| Probabilistic Methods in Computer Science | ||
| Design and Analysis of Algorithms | ||
or other Computer Science courses approved by the concentration advisor | ||
Three of the following: | ||
| Introduction to Computer Systems | ||
or CSCI 0320 | Introduction to Software Engineering | |
| Introduction to Software Engineering | ||
| Algorithmic Foundations of Computational Biology | ||
| Statistical Methods in Bioinformatics, I | ||
| Statistical Inference II | ||
| Foundations of Population Genetics | ||
| Computational Methods for Studying Demographic History with Molecular Data | ||
| Human Population Genomics | ||
| Computational Probability and Statistics | ||
| Biological Sciences track | ||
At least four courses comprising a coherent theme in one of the following areas: Biochemistry, Ecology, Evolution, or Neurobiology. | ||
AND select two courses from the following: | ||
| Statistical Inference II | ||
| Computational Probability and Statistics | ||
| Foundations of Population Genetics | ||
| Computational Methods for Studying Demographic History with Molecular Data | ||
| Human Population Genomics | ||
| Machine Learning | ||
| Deep Learning | ||
| Algorithmic Foundations of Computational Biology | ||
| Statistical Methods in Bioinformatics, I | ||
| Applied Mathematics & Statistics Track: | ||
At least three courses from the following: | ||
| Statistical Inference II | ||
| Computational Probability and Statistics | ||
| Artificial Intelligence | ||
| Methods of Applied Mathematics II and Methods of Applied Mathematics I | ||
OR | ||
| Applied Partial Differential Equations I and Applied Ordinary Differential Equations | ||
At least three of the following: | ||
| Quantitative Models of Biological Systems | ||
| Foundations of Population Genetics | ||
| Computational Methods for Studying Demographic History with Molecular Data | ||
| Human Population Genomics | ||
| Machine Learning | ||
| Deep Learning | ||
| Algorithmic Foundations of Computational Biology | ||
| Statistical Methods in Bioinformatics, I | ||
| Total Credits | 18-20 | |
Honors:
In order to be considered a candidate for honors, students will be expected to maintain an outstanding record, with no "C's" in concentration courses and with a minimum of an "A-" average in concentration courses. In addition, students should take at least one semester, and are strongly encouraged to take 2 semesters, of reading and research with a CCMB faculty member or approved advisor. Students must submit to a public defense of their theses to be open to the CCMB community.
- Students seeking honors are advised to choose a Thesis Advisor prior to the end of their Junior year
- Students must complete the Registration form for Comp Bio and submit it to CCMB@BROWN.EDU
Any deviation from these rules must be approved by the director of undergraduate studies, in consultation with the student's advisor.