S* Lecturers

Genomics, Central Paradigm, Smith-Waterman, EMOTIF.

An introduction to sequence alignment and algorithms to align sequences. An overview of some topics pertinent to sequence alignment is covered: difference between similarity and homology, relationship between sequence and structure. An example of pairwise sequence & multiple alignment using the Needleman-Wunsch and Tulla algorithms, respectively, are given with cautionary caveats about the limits of alignment.

A review of technologies, applications, and challenges in comparative genomics. What are the features of genomes to be compared? What can we do with genome comparison results - in particular, how do we construct protein interaction maps based on gene fusion events? How can we align genome-scale sequences efficiently?

Focus on transcript analysis and reconstruction from a sequence perspective.

Genetics Networks, Studying Gene Networks, DNA and/or RNA Annealing, What to do with Array Data, Average of Clustered Wave Forms, Reconstructing Genetic Network, Simplification: Boolean Network, Sample Network, Some Sample State Transitions, Finite State Automata, Correspondence, Biological Roles RNA, RNA Function, Tertiary Structure, Looking for Covariation, RNA Folding Energetics, Dot Plot Approach, Simple Energies.

Course Outline, Principles of Biology, Energy Landscapes, What Does A Protein Look Like?, See The Protein Alone, What Is An Atom?, What Is A Molecule?, Bond Stretching, Electrostatics Interaction, Advanced Physical Principles, Hydrophobic Effect, Dielectric Effect.

An introduction to basic protein structure: basic protein chemistry, visualization, protein structure (primary, secondary, tertiary, quaternary), secondary structural elements, folds & fold classification, packing.

An introduction to basic protein structure, structure determination and problems which motivate the development of computational approaches to structure prediction, including secondary structure prediction, ab initio structure prediction, fold family recognition or threading approaches and homology modeling. Some of problems with computational prediction methods are discussed briefly.

This lecture gives a theoretical overview of molecular docking, with an emphasis on the computational study of macromolecular systems.

This lecture provides practical knowledge of how to model and solve docking problems, particularly for protein interactions with small molecules.