The mission of the Center for Computational Molecular Biology (CCMB) is to make breakthrough discoveries in the life sciences through the development and application of novel computational, mathematical, and statistical techniques. Research in the Center aims to exploit the opportunities from technological advances in genomics and proteomics.

For more information please visit www.brown.edu/ccmb

## Computational Biology

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 | |

Introductory Calculus, Part II | ||

or MATH 0170 | Advanced Placement Calculus | |

The Foundation of Living Systems | ||

General Core Requirements: Biology | 2 | |

Genetics | ||

Introductory Biochemistry | ||

or BIOL 0500 | Cell and Molecular Biology | |

General Core Requirements: Chemistry | 1 | |

Equilibrium, Rate, and Structure | ||

or CHEM 0350 | Organic Chemistry | |

General Core Requirements: Computer Science | 2 | |

Introduction to Object-Oriented Programming and Computer Science and Introduction to Algorithms and Data Structures | ||

OR | ||

Computer Science: An Integrated Introduction and Computer Science: An Integrated Introduction | ||

OR | ||

Accelerated Introduction to Computer Science and Computer Science: An Integrated Introduction and Introduction to Software Engineering and Introduction to Computer Systems and Theory of Computation | ||

General Core Requirements: Probability & Statistics | 1 | |

Statistical Inference I | ||

OR | ||

Probability and Computing | ||

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 | ||

Computational Theory of Molecular Evolution and Population Genetics | ||

Human Population Genomics | ||

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 | Introductory Calculus, Part II (or equivalent) | 1 |

or MATH 0170 | Advanced Placement Calculus | |

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 | Introductory 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 | |

General Core Requirements: Computer Science | 2-4 | |

Introduction to Object-Oriented Programming and Computer Science and Introduction to Algorithms and Data Structures | ||

OR | ||

Computer Science: An Integrated Introduction and Computer Science: An Integrated Introduction | ||

OR | ||

Accelerated Introduction to Computer Science and Computer Science: An Integrated Introduction and Introduction to Software Engineering and Introduction to Computer Systems | ||

CSCI 0220 | Introduction to Discrete Structures and Probability | 1 |

General Core Requirements: Probability & Statistics | ||

APMA 1650 | Statistical Inference I | 1 |

or CSCI 1450 | Probability and Computing | |

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 | ||

Applied Artificial Intelligence | ||

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 | |

Algorithmic Foundations of Computational Biology | ||

Statistical Methods in Bioinformatics, I | ||

Statistical Inference II | ||

Computational Theory of Molecular Evolution and Population Genetics | ||

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: | ||

Algorithmic Foundations of Computational Biology | ||

Statistical Methods in Bioinformatics, I | ||

Statistical Inference II | ||

Computational Theory of Molecular Evolution and Population Genetics | ||

Human Population Genomics | ||

Computational Probability and Statistics | ||

Applied Mathematics & Statistics Track: | ||

At least three courses from the following: | ||

Statistical Inference II | ||

Computational Probability and Statistics | ||

Applied Artificial Intelligence | ||

Methods of Applied Mathematics I, II and Methods of Applied Mathematics I, II | ||

OR | ||

Applied Partial Differential Equations I and Applied Ordinary Differential Equations | ||

At least three of the following: | ||

Computational Theory of Molecular Evolution and Population Genetics | ||

Algorithmic Foundations of Computational Biology | ||

Statistical Methods in Bioinformatics, I | ||

Quantitative Models of Biological Systems | ||

Human Population Genomics | ||

Total Credits | 18-20 |

*Honors:*

*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.

## Computational Biology

The Center for Computational Molecular Biology (CCMB) offers a Ph.D. program in Computational Biology to train the the next generation of scientists to perform cutting edge research in the multidisciplinary field of computational biology. During the course of their Ph.D. studies students will develop and apply novel computational, mathematical , and statistical techniques to problems in the life sciences.

The Ph.D. program in Computational Biology encompasses three individual training programs with a core of common requirements and specific requirements from individual departments of Computer Science, Molecular, Cell Biology & Biochemistry (MCB), and Ecology and Evolutionary Biology (EEB). Applicants should state a preference for one of these three programs. In addition, students interested in the intersection of Applied Mathematics and Computational Biology are encouraged to apply directly to the Applied Mathematics Ph.D. program, and also to contact relevant CCMB faculty members.

The Computational Biology Ph.D. program assumes the following prerequisites: mathematics through intermediate calculus, linear algebra and/or discrete mathematics, demonstrated programming skill, and at least on undergraduate course in chemistry and in molecular biology. Exceptional strengths in one area may compensate for limited background in other areas, but some proficiency across the disciplines must be evident for admission.

The application process to the CCMB graduate program is run through the Graduate School (http://www.brown.edu/academics/gradschool/)