Seminar on Computational Biology

Spring 2021 Course
Seminar on Computational Biology: Focus on SARS-Cov-2 and COVID-19

Course
								Welcome
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Spring 2021 -- CS 590-01/CBB 590-01 -- Tuesday 1:45 Pm -- Prof. Bruce Donald

Abstract: This year's seminar will focus on COVID-19, SARS-CoV-2, and Therapeutic Design. However, background material and fundamental basic science, algorithms, and computational methods will be covered in order to get to the foothills of this field.

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.

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.

Click here for class overview, schedule, details, etc.


COMPSCI 590-01 and CBB 590-01
Spring 2021
*Crosslisted as CBB 590-01


We will meet:

Instructor: Bruce Donald (www.cs.duke.edu/brd/)
Office hours: Tues After Class, stay on same Zoom Link
Tuesday after class is the best office hour time to meet. Or you can email me with questions or for another time.

Class Webpage: www.cs.duke.edu/donaldlab/Teaching/Seminar21/


Overview | Syllabus | Schedule | How to give a good talk
Supplemental Materials | Some Relevant WWW Links | Recitation Materials

Course Summary/Syllabus:

          "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 and CBB 590.

      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.

      This year we will focus on COVID-19, SARS-CoV2, and Therapeutic Design. However background material and fundamental basic science and computational methods will be covered in order to get to the foothills of this field.

      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.

      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.

      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.

      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!

      Textbooks:

      1. Algorithms in Structural Molecular Biology, MIT Press (Cambridge: 2011), 464 pp. ISBN: 0262015595. Available from Duke Libraries here and (On reserve from Duke Library).

      2. Methods in Protein Design. In: Methods in Enzymology, Vol. 523. (2013). ISBN: 9780123942920.
      Algorithms in Structural Molecular Biology,  MIT Press (2011)