COMPSCI 260: Introduction to Computational Genomics

Overview

A computational perspective on the exploration and analysis of genomic and genome-scale information. Provides an integrated introduction to genome biology, algorithm design and analysis, and probabilistic and statistical modeling. Topics include genome sequencing, genome sequence assembly, read mapping, local and global sequence alignment, sequence database search, gene finding, phylogenetic tree construction, and elementary gene expression analysis. Methods include dynamic programming, indexing, hidden Markov models, and elementary supervised machine learning. Focuses on foundational algorithmic principles. Development of practical experience with handling, analyzing, and visualizing genomic data using the computer language Python.

The course requires students to program often in Python. Students coming in to the course must already know how to program in some computer language, but it need not be Python. If it is not Python, students will be expected to come quickly up to speed in Python on their own. Additionally, students should be comfortable with mathematical thinking and formulas, and should have had some exposure to basic probability as well as molecular or cellular biology; however, the course has no formal course prerequisites, and quick refreshers of relevant background will be provided. Please speak to the instructor if you are unsure about your background. This course is a valid elective in both biology and computer science.

Staff

Professor Alex Hartemink

Webpage: http://www.cs.duke.edu/~amink
Email: amink at cs.duke.edu
Office Location: LSRC D239
Office Phone: (919) 660-6514

Derrick Adam, TA Email: derrick.adam at duke.edu
Kyle Pinheiro, TA Email: kyle.pinheiro at duke.edu
Nhat Duong, TA Email: nhat.duong at duke.edu
Abbey List, UTA Email: abbey.list at duke.edu
Andrew Lee, UTA Email: andrew.j.lee at duke.edu
Angela Yoon, UTA Email: angela.yoon at duke.edu
Bianca Saputra, UTA Email: bianca.saputra at duke.edu
Caleb Watson, UTA Email: caleb.watson at duke.edu
Cynthia Wang, UTA Email: cynthia.wang2 at duke.edu
Jake Spruance, UTA Email: jacob.spruance at duke.edu
Kash Sreeram, UTA Email: kashyap.sreeram at duke.edu
Matthew Lee, UTA Email: matthew.h.lee at duke.edu
Vin Somasundaram, UTA   Email: vineethsubbu.somasundaram at duke.edu

Office hours

Office hours with TAs and UTAs will be held at the following times, starting on Thursday 13 January; most days of the week have either two or three sessions available, with the exceptions of Tuesday (no sessions) and Wednesday (one session). We have arranged for a balanced mix of online sessions (which will be conducted over Zoom) and in-person sessions (which will take place in Perkins Link Group Study 8: PLGS8). Note that in accordance with current university guidance about remote learning at the start of the semester, all office hours from 13–17 January will be conducted over Zoom; any in-person session listed below will start to be held in-person on 18 January.

Directions for how to access office hours over Zoom will be posted on Ed. Remember that you will get help quickest by asking your questions on Ed (in fact, your question may already be answered there).

If you would like to speak with the instructor about anything, you are welcome to stick around after lecture to chat, or you can send an email to schedule a meeting at a time that is convenient for you.

Logistics

The class meets on Tuesdays and Thursdays 10:15–11:30AM in 111 BioSci. Duke has announced that class sessions before January 18 will be virtual. These and any other virtual sessions will be held over Zoom. The Zoom link can be found on the COMPSCI 260 site within Sakai.