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
Textbook(s):
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)