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: 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 |

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 four tracks: | 6 | |

Computer Science Track: | ||

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 and Introduction to Software Engineering | ||

OR | ||

Algorithmic Foundations of Computational Biology | ||

Statistical Methods in Bioinformatics, I | ||

Statistical Inference II | ||

Computational Theory of Molecular Evolution and Population Genetics | ||

Human Population Genomics | ||

Biological Sciences track | ||

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 | ||

Computational Theory of Molecular Evolution and Population Genetics | ||

Human Population Genomics | ||

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 Applied Ordinary Differential Equations | ||

OR | ||

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

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:*

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.