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 doctoral program is interdepartmental and the result of a collaboration between the four academic units that comprise the CCMB: Applied Mathematics, Computer Science, Ecology & Evolutionary Biology, and Molecular Biology, Cell Biology & Biochemistry.

The Undergraduate program offers four possible 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.

**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 | ||

CHEM 0330 | Equilibrium, Rate, and Structure | 1 |

BIOL 0470 | Genetics (prerequisite BIOL 0200 or equivalent) | 1 |

BIOL 0280 | Introductory Biochemistry | 1 |

or BIOL 0500 | Cell and Molecular Biology | |

CSCI 0150 | Introduction to Object-Oriented Programming and Computer Science (no prerequisite) | 1 |

CSCI 0160 | Introduction to Algorithms and Data Structures (prerequisite CSCI 0150) | 1 |

or CSCI 0170 | Computer Science: An Integrated Introduction | |

CSCI 0180 | Computer Science: An Integrated Introduction (prerequisite CSCI 0170) | 1 |

or CSCI 0190 | Accelerated Introduction to Computer Science | |

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

APMA 1650 | Statistical Inference I | 1 |

Computational Biology Core Course Requirements | ||

CSCI 1810 | Computational Molecular Biology (prerequisites: (CSCI 0160, or CSCI 0180, or CSCI 0190) and CSCI 0220) | 1 |

APMA 1080 | Inference in Genomics and Molecuar Biology | 1 |

Capstone Experience ^{1} | 1 | |

Directed Research/Independent Study | ||

Individual Independent Study | ||

Six courses in one of the following four tracks: | 6 | |

Computational Genomics Track: ^{2} | ||

Three of the following: | ||

Introduction to Computer Graphics | ||

Database Management Systems | ||

Applied Artificial Intelligence | ||

Probability and Computing: Randomized Algorithms and Probabilistic Analysis | ||

Design and Analysis of Algorithms | ||

or other Computer Science courses approved by the concentration advisor | ||

Three of the following: | ||

Introduction to Computer Systems | ||

Introduction to Software Engineering | ||

Algorithmic Foundations of Computational Biology | ||

Statistical Methods in Bioinformatics, I | ||

Statistical Inference II | ||

The Computational Theory of Molecular Evolution | ||

Biological Sciences track ^{3} | ||

At least four courses comprising a coherent theme in one of the following areas: Biochemistry, Ecology, Evolution, or Neurobiology. | ||

Select two courses from the following: | ||

Algorithmic Foundations of Computational Biology | ||

Statistical Methods in Bioinformatics, I | ||

Statistical Inference II | ||

The Computational Theory of Molecular Evolution | ||

Molecular Modeling Track: ^{4} | ||

Computational Tools in Biochemistry and Chemical Biology | ||

At least three courses from the following: | ||

Physical Chemistry: Thermodynamics and Statistical Mechanics | ||

Chemical Biology | ||

or CHEM 1240 | Biochemistry | |

or BIOL 1270 | Advanced Biochemistry | |

Principles of Immunology | ||

Physiological Pharmacology | ||

Molecular Genetics | ||

Two courses from the following: | ||

Algorithmic Foundations of Computational Biology | ||

Statistical Methods in Bioinformatics, I | ||

Statistical Inference II | ||

The Computational Theory of Molecular Evolution | ||

Applied Mathematics and Statistical Genomics Track: ^{5} | ||

At least three courses from the following: | ||

Statistical Inference II | ||

Computational Probability and Statistics | ||

Applied Artificial Intelligence | ||

Methods of Applied Mathematics I, II | ||

Methods of Applied Mathematics I, II | ||

At least three of the following: | ||

The Computational Theory of Molecular Evolution | ||

Algorithmic Foundations of Computational Biology | ||

Statistical Methods in Bioinformatics, I | ||

Quantitative Models of Biological Systems | ||

Total Credits | 19 |

^{1} | 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. A minimum of one semester of independent study is required, although many students may conduct a full year of independent study. |

^{2} | This track is designed for students whose interests lie in the development of algorithms and high-quality software (tools and systems) for biological applications. |

^{3} | This track is designed for students whose interests lean more towards biological questions. |

^{4} | This track is designed for students who wish to gain competence in the field of molecular modeling and drug design. |

^{5} | This track is designed for students whose interest focuses on extracting information from genomic and molecular biology data, and modeling the dynamics of these systems. Substitution of more advanced courses with consent of advisor is permitted. |

*Honors:*

*Honors:*

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.