High-throughput experimental approaches now allow molecular biologists to make
large-scale measurements of DNA, RNA, and protein, the three fundamental molecules
of the cell. The resulting datasets are often too large for manual analysis and
demand computational techniques. This course introduces algorithms for sequence
comparison and alignment; molecular evolution and phylogenetics; DNA/RNA sequencing
and assembly; recognition of genes and regulatory elements; and RNA and protein
structure. The course demonstrates how to model biological problems in terms
of computer science.
CSCI1820: Algorithmic Foundations of Computational Biology
The course is devoted to computational and statistical methods as well as software
tools for DNA, RNA, and protein sequence analysis. The focus is on understanding
the algorithmic and mathematical foundations of the methods, the design of associated
genomics software tools, as well as on their applications. Topics include: sequence
alignment, genome assembly, gene prediction, regulatory genomics, and SNP's variation.
CSCI2820: Advanced Algorithms in Computational Biology and Medical
Bioinformatics
Devoted to computational problems and methods in the emerging field of Medical
Bioinformatics where genomics, computational biology and bioinformatics impact
medical research. We will present challenging problems and solutions in three
areas: Disease Associations, Protein Folding and Immunogenomics.