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Genomics Spring 2012 Course Description
This course is designed for beginning students who want to become familiar with the basic concepts and applications of genomics. The course covers a wide range of topics including how genomes are mapped and sequenced as well as the latest computational and experimental techniques for predicting genes, splice sites, and promoter elements. High throughput techniques for ascribing function to DNA, RNA, and protein sequences including microarrays, Next Generation Sequencing, mass spectrometry, interspecies genome comparisons and genome-wide knock-out collections will also be discussed. Finally, the use of genomic techniques and resources for studies of human disease will be discussed.
A heavy emphasis will be put on students acquiring the basic skills needed to navigate databases that archive sequence data, expression data and other types of genome-wide data. Through problem sets the students will learn to manipulate and analyze the large data sets that accompany genomic analyses by writing simple computer scripts. While students will become sophisticated users of computational tools and databases, programming and the theory behind it are covered elsewhere, in Michael Brent’s class, Bio 5495 Computational Molecular Biology.
Because of limited space in our teaching lab, enrollment for lab credit will be limited to 24 students. Priority will be given to students in the DBBS program. Others interested in the course may enroll for the lectures only. If you have previous experience in computer programming, we ask that you do not enroll for the laboratory credit.
Lectures:
Mon, Wed 10:00-11:30 am
Rm 5206, 4444 Forest Park Blvd.
Computer Lab:
Fri., 10:00-11:30 am
Rm 5206, 4444 Forest Park Blvd.
Course Masters:
Ting Wang, twang@genetics.wustl.edu, Rm 6203, 4444 Forest Park Blvd.
Donald Conrad, dconrad@genetics.wustl.edu
Teaching Assistants:
Mark Charbonneau, mcharbo@wustl.edu
Kevin Forsberg, kjforsbe@wustl.edu
Textbooks and Resources
Although there will be a heavy emphasis on bringing students up to speed in the computational skills neccessary to analyze genome-wide data, we do not assume that students have extensive computer skills. Those students who are not familar with command line operating systems (Unix, Linux) or basic programming should should look through John McCutcheon’s Linux Primer.
Here is a quick unix reference sheet.
This class will teach students to write simple scripts using Perl. Students are strongly recommended to review online an introductory text:
Picking Up Perl or Beginning Perl
Here is a short perl tutorial.
Those of us that use Perl and Linux on a frequent basis to navigate through large biological datasets find the following texts helpful as well.
Learning Perl, Tom Phoenix, Randal L. Schwartz, O’Reilly Media
Programming Perl, Larry Wall, Tom Christiansen and John Orwant, O’Reilly and Associates, Inc
Perl By Example, Ellie Quigley, Prentice Hall
Perl Cookbook, Tom Christiansen and Nathan Torkington, O’Reily and Associates, Inc
Linux in a Nutshell , Ellen Siever, O’Reilly and Associates, Inc
Bioinformatics, David Mount, Cold Spring Harbor Press
Introduction to the Practice of Statistics, David Moore and George McCabe, W.H. Freeman and Company
Page last modified 12/08/2011.
Genomics Spring 2012 Course Description
This course is designed for beginning students who want to become familiar with the basic concepts and applications of genomics. The course covers a wide range of topics including how genomes are mapped and sequenced as well as the latest computational and experimental techniques for predicting genes, splice sites, and promoter elements. High throughput techniques for ascribing function to DNA, RNA, and protein sequences including microarrays, Next Generation Sequencing, mass spectrometry, interspecies genome comparisons and genome-wide knock-out collections will also be discussed. Finally, the use of genomic techniques and resources for studies of human disease will be discussed.
A heavy emphasis will be put on students acquiring the basic skills needed to navigate databases that archive sequence data, expression data and other types of genome-wide data. Through problem sets the students will learn to manipulate and analyze the large data sets that accompany genomic analyses by writing simple computer scripts. While students will become sophisticated users of computational tools and databases, programming and the theory behind it are covered elsewhere, in Michael Brent’s class, Bio 5495 Computational Molecular Biology.
Because of limited space in our teaching lab, enrollment for lab credit will be limited to 24 students. Priority will be given to students in the DBBS program. Others interested in the course may enroll for the lectures only. If you have previous experience in computer programming, we ask that you do not enroll for the laboratory credit.
Lectures:
Mon, Wed 10:00-11:30 am
Computer Lab:
Fri., 10:00-11:30 am
Course Masters:
Ting Wang, twang@genetics.wustl.edu, Rm 6203, 4444 Forest Park Blvd.
Donald Conrad, dconrad@genetics.wustl.edu
Teaching Assistants:
Mark Charbonneau, mcharbo@wustl.edu
Kevin Forsberg, kjforsbe@wustl.edu
Textbooks and Resources
Although there will be a heavy emphasis on bringing students up to speed in the computational skills neccessary to analyze genome-wide data, we do not assume that students have extensive computer skills. Those students who are not familar with command line operating systems (Unix, Linux) or basic programming should should look through John McCutcheon’s Linux Primer.
Here is a quick unix reference sheet.
This class will teach students to write simple scripts using Perl. Students are strongly recommended to review online an introductory text:
Picking Up Perl or Beginning Perl
Here is a short perl tutorial.
Those of us that use Perl and Linux on a frequent basis to navigate through large biological datasets find the following texts helpful as well.
Learning Perl, Tom Phoenix, Randal L. Schwartz, O’Reilly Media
Programming Perl, Larry Wall, Tom Christiansen and John Orwant, O’Reilly and Associates, Inc
Perl By Example, Ellie Quigley, Prentice Hall
Perl Cookbook, Tom Christiansen and Nathan Torkington, O’Reily and Associates, Inc
Linux in a Nutshell , Ellen Siever, O’Reilly and Associates, Inc
Bioinformatics, David Mount, Cold Spring Harbor Press
Introduction to the Practice of Statistics, David Moore and George McCabe, W.H. Freeman and Company
Page last modified 12/08/2011.