In a certain sense, many fundamental biological processes can be viewed as performing computation and communication (e.g., gene transcription and regulation). From this point of view, it is interesting to ask what application computational methods have in deciphering and understanding biological processes. We will look at how computational approaches have played an active role in helping us understand biological processes, and how these approaches may even inform our understanding of the processes themselves.
More specifically, advances in experimental techniques have enabled the study of biological phenomena on a larger scale and higher resolution than previously possible; high throughput microarray experiments, nuclear magnetic resonance spectroscopy, and high-resolution X-ray crystallography are just a few examples. We will study how these advances in technology require
computational techniques to understand and use this data in making biological discoveries. We will also cover applications in which computational techniques play a primary role in biological discovery; two well-known examples are DNA fragment assembly and rational drug design. Examples of other computational techniques that we will cover in this seminar are microarray analysis, molecular dynamics simulations, protein structure prediction and determination, all of which are routinely used to develop, guide, and check biological hypotheses.
In general, the class will be a survey of topics in genomics (the study of DNA sequences) and proteomics (the study of protein structure and function) research. If time permits, we will also have guest speakers who will discuss computational techniques in specific application areas. We will cover the following topics, roughly in this order:
- Sequence Assembly
- Gene Finding and Microarray Analysis
- Molecular Dynamics Protein Structure Prediction, and Protein Design
- Protein Structure Determination via X-ray crystallography and Nuclear Magnetic Spectroscopy
- Protein-Ligand Binding, Drug Design, and Protein-Protein Interactions and Docking
- Interaction Networks, Neural Modeling
- Phylogenetics and Protein Evolution
No previous knowledge of biology or biochemistry will be assumed; we will spend the first few weeks of class covering the prerequisite material. However, experience with computational techniques in another discipline will be quite useful. The course grade will be determined by student presentations and a semester project. The semester project will be a writeup that summarizes a specific topic that was covered in class, and discusses and/or defines open problems.
Lectures notes
| Reading | Class Topic |
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| — | President's Day |
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| | Gene Finding/Microarray Analysis (PDF) |
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| — | Theory and Practice of Molecular Dynamics |
| — | Spring Break |
| — | Spring Break |
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| — | Protein Structure Prediction |
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| — | Protein Redesign for Allostery |
| — | Class Cancelled |
| | Computation of Protein Geometry (PDF) |
| — | Computation of Protein Geometry |
| — | Patriot's Day |
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| — | Homology Modeling via Protein Threading |
| — | X-Ray Crystallography (PDF) |
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| — | NMR Data and Protein-Protein Docking |
| | Evolutionary Analysis of Protein Structure |
| — | Evolutionary Analysis of Protein Structure |
| | Graph-based Approaches to Interpreting Biological Networks |
| — | Graph-based Approaches to Interpreting Biological Networks |
| | Applications of Control Theory to Analyzing Biological Networks |
| — | Applications of Control Theory to Analyzing Biological Networks |
