Course Summary:

"Strictly speaking, molecular biology is not a new discipline, but rather a new way of looking at organisms as reservoirs and transmitters of information. This new vision opened up possibilities of action and intervention that were revealed during the growth of genetic engineering."

- Michel Morange, "A History of Molecular Biology," Harvard University Press.
Some of the most challenging and influential opportunities for Physical Geometric Algorithms (PGA) arise in developing and applying information technology to understand the molecular machinery of the cell. Recent work shows that PGA techniques may be fruitfully applied to the challenges of structural molecular biology and rational drug design. Concomitantly, a wealth of interesting computational problems arise in proposed methods for discovering new pharmaceuticals.

NB: This course is cross listed as Compsci 590.01 and CBB 590.01. There is a glitch with the paperwork/Duke Hub so if you do not see the CBB one sign up for the Compsci one. Do not be alarmed. They are exactly the same class and if you like you can switch later.

This seminar course focuses on topics in computational biology. We will emphasize themes that unite algorithms, modelling, and experimental results. Topics will include algorithms, modeling, and experimental validation for several areas, including protein design, protein:protein interactions, structural biology, structural immunology, and structure-based drug design.

For those who have taken a class or seminar with me previously, this semester we will read entirely different papers, so please feel free to sign up.

To give you an idea about the kind of papers we will read, here is the schedule from last year. Note that we will read different papers this year! This is just to give you an idea!

Graduate students and undergraduate students are welcome in this class. In this class I welcome students from diverse backgrounds: computer science, biochemistry, biology, chemistry, engineering, physics... It is recommended that students be interested in the connections between computational science and the life sciences as applied to macromolecules of biological and pharmacological importance.

In this seminar course students will present both recent and classic papers from the literature, and also compile notes on these papers.

Class will end in plenty of time for students to attend the SBB Seminar.

The primary reading for this course will be supplied as papers to the students. While some of the background for these papers may be unfamiliar, the class is structured so that students can acquire this background while preparing to present and discuss the papers. Specifically, students will read a textbook, that is designed for this course, in order to prepare for and understand the background to present the papers. One textbook covers basic algorithms in this area of computational biology, and their applications. The second covers recent results in the field of protein design. When the weekly papers are assigned, relevant chapters of the textbooks will be assigned as area/background reading. However, student presentations will concentrate on the papers, not on presenting from the textbooks.

Textbooks:

1. Algorithms in Structural Molecular Biology, MIT Press (Cambridge: 2011), 464 pp. ISBN: 0262015595.

2. Methods in Protein Design. In: Methods in Enzymology, Vol. 523. (2013). ISBN: 9780123942920.
   • store.elsevier.com/Methods-in-Protein-Design/isbn-9780123942920/
   • Also available on the Duke Libraries site. Go to library.duke.edu/search?id=DUKE005910490 and click on the "get it @ Duke" button.


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