Course Overview

    Genetics 875:Genomic and Proteomic Analysis –Fall 2012 (3 credits)

    Monday/Wednesday Lecture: 2:25-3:15 pm; Genetics/Biotechnology Center - Rm 1408

    Monday Computer Lab:3:30 – 5:30 pm; DMC Computer Lab in *New Biochemistry, 420 Henry Mall

    Course wiki: http://akka.genetics.wisc.edu/groups/genetics875/


    Nicole Perna, ntperna@wisc.edu, 4434 Biotech Addition, Phone: 890-0171

    Audrey Gasch agasch@wisc.edu, 3426 Biotech Addition, Phone:265-0859


    With the availability of genome sequences and high-throughput techniques, organismal physiology can now be examined on a global scale by monitoring the behavior of all genes or proteins in a single experiment. This course will present modern techniques in genomics and proteomics, with particular focus on analyzing the data generated by these techniques. Course material will cover genomic sequencing, comparative sequenceanalysis, phylogeny construction and phylogenomics, transcription factor motif discovery, DNA microarray analysis, techniques in mass spectrometry,proteomic screening methods, and protein-interaction network analysis.

    In addition to lecture time, the course includes a weekly computer lab where students get hands-on experience analyzing genomic and proteomic datasets.In addition, students conduct a semester-long computational project of their choice that uses multiple computational methods discussed in class.


    60%:Class Project

    10% One page project summary - due Oct. 3

    20% Two-three page description of methods and preliminary results - due Nov. 7

    30% Seven-ten page final paper (with additional pages for figures and references) in manuscript format - due Dec. 5

    20% Labs/Homeworks - announced weekly

    20% Attendance/Discussion

    Class Paper:

    The final class paper should be 7-10 pages (1.5 line spacing), with additional pages for figures and references, in manuscript format (e.g. Introduction, Materials and Methods, and Results and Discussion). Extensive writing on the data collection is not necessary (e.g. buffer conditions,etc) but a sufficient description of the generated or published datasets should be given. Cite clearly what data processing or analysis was done by you versus others (especially if using published datasets where some analysis has already been done).

    Final Class Presentation (Dec 10 & Dec 12):

    In the last week of class, each student will give a 7 minute presentation (with 2 additional minutes for questions) on

    their class project. The goal is to give 1-2 slides of background with the rest of the presentation focusing on methods,

    results, and challenges.


    Readings and labs will be posted on the web site.

    Attendance is expected unless you give prior notice of a conflict.

    Assignments must be turned in on time.Two or more late assignments will affect your overall course grade.

    Collaborative work is encouraged, but you need to list all contributors.

    Participation is required and factored into the final grade. An A grade for the course requires significant participation in lecture discussions.