Carnegie Mellon University

Fundamentals of Bioinformatics

Course Number: 02-604

This course is designed for first-year MS students in computational biology or students from other disciplines who desire a broad introduction to some of the most fundamental algorithmic approaches in analyzing the large datasets generated from experiments in molecular biology.

A solid background in introductory programming (such as that provided by 02-601) is essential.  Some knowledge of basic algorithms and data structures is also helpful.  Background biology knowledge is not needed.

Key Topics:

Identifying replication origins in bacterial genomesRandomized algorithms for motif finding in DNA sequences

Graph-based algorithms for genome assembly

Brute-force algorithms for antibiotic analysis

Dynamic programming algorithms for sequence alignment

Combinatorial algorithms for genome rearrangement analyses

Evolutionary tree construction algorithms

Clustering algorithms for gene expression analyses

Combinatorial pattern matching algorithms applied to DNA read mapping

Hidden Markov models for comparing rapidly mutating genetic sequences

Statistical analysis for computational proteomics

Semester(s): Spring
Units: 12


Course Companion

Sample Lecture Recordings

Assessment Structure:

Comprehension quizzes. (10% of grade)Weekly write up and participation (10% of grade)
Programming assignments. (40% of grade)
Bioinformatics Software challenges. (10% of grade)
Midterm. (10% of grade)
Final exam (20% of grade)