Exam 2 Take Home Due Friday May 6
Exam 1 Take Home Due Monday March 21
Exam 1 Reading Guide and Sample Questions
Some presentations you might find useful
Intro to HMMs and Gene Finding
Bioinformatics2004 (PowerPoint) (pdf) WARNING: These files are huge (250+ pages)
Optional Homework Problems (Not graded or turned in, but we can discuss any of these in class as you feel the need)
HIV.phy (data file in PHYLIP sequential format)
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Instructor:
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Spencer Muse
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Lecture:
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MW 9:10 – 10:00
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1515 Partners II
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328 Withers Hall
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Lab:
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F 9:10 – 10:00
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515-1948
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G100 Harrelson
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Course Webpage:
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www.stat.ncsu.edu/~muse
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Textbook:
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Bioinformatics: Sequence and Genome Analysis, by David Mount
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By design, this course is not a rigorous course in statistics, mathematics, computer science, or genetics, although we will use concepts from each of those fields. Roughly eight major areas will be covered during the course. In each section we will begin with the biological motivation. From there, we will move to either a computational or statistical treatment of the topic; in some cases we will explore both. By necessity, we will not have in-depth treatments. Instead, the goal is to provide a basic understanding of the basic problems facing bioinformaticists, and a sampler of some of the computational and statistical tools that are used to solve those problems.
We will meet each Friday in G100 Harrelson (ground floor Unix lab). On many but not all of those days we will look at web-based bioinformatics resources. On roughly half of the Fridays we will have a regular lecture. Learning the nuts and bolts of a wide range of software and databases is not a goal of this class, although we will certainly learn to use some important bioinformatics tools. There will be no computer programming in the class.
There are no formal prerequisites for the course. However, it is assumed that students will have some background in either molecular genetics (GN 411) or statistics (ST 511 or ST 521). Students with no background in either of these subjects have been successful in the course in the past, but have had to do a lot of extra reading.
Because of the diversity in your backgrounds, we will begin the course with some background material in genetics, probability, and statistics. Most of you will find some parts of the course to be a simple review and other parts completely foreign; hopefully most of the time you will find yourself somewhere in between those two extremes. The diversity of interests and backgrounds usually makes for lively discussion from different perspectives, so please speak up and contribute!
We will have a midterm exam on or around March 18, and a final exam on May 6. Each exam will be worth 50 points, and each will consist of an in class and take-home portion. I will give HW assignments with posted solutions, but these will not be turned in for grading.
Week
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Topic
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Reading
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Jan
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10 12 14
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Background
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Ch. 1, 2
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24 26 28
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Sequence Alignment
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Ch. 3,4
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Feb
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31 2 4
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7 9 11
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14 16 18
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Database Searching
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Ch 6
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21 23 25
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Multiple Alignment I
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Ch. 5
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Mar
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28 2 4
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Hidden Markov Models
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Spring Break
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14 16 18
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Multiple Alignment II
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21 23 |
Phylogeny
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Ch. 7
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Apr
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28 30 1
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4 6 8
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Gene Finding
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Ch. 9
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11 13 15
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Genome Analysis
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Ch. 11,13
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18 20 22
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25 27 29
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