BINF 733 Spring 2007
Microarry Analysis
Instructor - Dr.Jeff
Solka (jlsolka@gmail.com)
Meeting Place -
Occoquan 327
Meeting Time - 7:20 – 10:00 pm
Tuesdays
Course Webpage
http://binf.gmu.edu/~jsolka/spring08/binf733/Spring_2007BINF_733_Microarray_Analysis_Syllabus_rev1.html
Course Description
Students will learn concepts needed
for correct experimental design of gene expression experiments in which
measurements are carried out using microarray platforms; students will
be
introduced to relevant data analysis techniques including preprocessing
(data
cleansing and handling missing values), appropriate data
standardization and
normalization methods within and between arrays; higher-level analyses
including dimensionality reduction, discriminant analysis, a variety of
clustering methods, annotation tools and visualization methods. These
methods
will be illustrated using the R computing environment and in particular
the
BioConductor packages developed for microarray analysis.
Course Goals Students
will be instructed in the
theoretical basis underlying a number of methods commonly used for
handling and
analyzing large datasets of molecular biological origin. These concepts
will be
reinforced with practical examples explained in class and reinforced
with
homework problems. Homework problems are selected to encourage students
to gain
facility using the R/BioConductor analysis packages and develop
analytical
skills for recognizing how to select an appropriate method from among
the large
number available. In some cases stand-alone tools will be discussed,
since
there is a large research literature in this topic. In addition to
chapters
from the course text, relevant research articles will be assigned, and
students
will be encouraged to critically dissect these papers for both
methodology and
results.
Grading Policy
Students will be evaluated for mastery of
course material through two homework assignments (50%), an in-class
presentation of a critical evaluation of a journal article (20%), and
an
in-class presentation (20%) with an accompanying formal written report
(10%) of
an analysis project (either replicating a published method in full or
modifying
such a method and comparing the students results to those of the
original
report).
Course Textbook-
"Bioinformatics and Computational Biology Solutions using R
and
BioConductor" by Robert Gentleman, V. Carey, W. Huber, Raphael
Irizarry,
and Sandrine Dudoit. (2005). The Springer Series in Statistics for
Biology and
Health.
"Microarray Bioinformatics," Dov Stekel (2003), Cambride Press.
Some Possible Papers for
Class Presentation -
Ramin
Homayouni,Kevin Heinrich, Lai Wei and
Michael W. Berry, "Gene Cluster by Latent Semantic Indexing of MEDLINE
Abstracts," Bioinformatics,Vol.
21 no. 1 2005, pages 104–115
Michael P. S. Brown, William Noble Grundy, David Lin,
Nello Cristianini, Charles Walsh Sugnet, Terrence S. Furey,
Manuel Ares, Jr., and David Haussler
"Knowledge-based analysis of microarray gene
expression data by using support vector machines
," PNAS,Vol.
97 no. 1 2000, pages 262–267
Pedro Carmona-Saez, Roberto D Pascual-Marqui,
F Tirado, Jose M Carazo, and Alberto Pascual-Montanocorresponding ,
"Biclustering of gene expression data by non-smooth non-negative matrix
factorization," BMC
Bioinformatics,Vol.
7 no. 78 2006
Alessandro
Di Cara, Abhishek Garg, Giovanni De Micheli, Ioannis Xenarios and Luis
Mendoza "Dynamic simulation of regulatory networks using SQUAD" BMC Bioinformatics,Vol.
8 no. 462 2007
Thomas
Thorne and Michael P.H. Stumpf "Generating confidence
intervals
on biological networks," BMC
Bioinformatics,Vol.
8 no. 467 2007
Jin-Dong
Kim, Tomoko Ohta and Jun'ichi Tsujii"Corpus annotation for mining
biomedical events from literature," BMC
Bioinformatics,Vol.
9 no. 10 2008
Gilad
Lerman and Boris E. Shakhnovich
"Defining functional distance using manifold embeddings of gene
ontology annotations," BMC
PNAS,Vol.
104 no. 27, pp. 11334–11339, 2007
Paolo E. Barbano, Marina Spivak, Marc Flajolet, Angus C. Nairn, Paul
Greengard,
and Leslie Greengard
"A mathematical tool for exploring the dynamics of biological
networks," BMC
PNAS, 2007
P. Glenisson, P. Antal, J. Mathys, Y. Moreau, B. De Moor,
"Evaluation of the Vector Space Representation in Text-Based Gene
Clustering,"
Pacific Symposium on
Biocomputing,Vol 8, pp. 391-402, 2003
Jarkko Venna and Samuel Kaski,
"Comparison of visualization methods for an atlas of gene
expression data sets,"
InfoVis06,2006
Nora Speer and Holger Fröhlich and Christian Spieth and Andreas Zell,
"Functional Grouping of Genes Using Spectral Clustering And Gene Ontology (2005),"
Proceedings of the IEEE International Joint Conference on Neural Networks,2005
Projected Class Schedule
Jan.
22, 2008 Introduction
to Bioconductor (Read Chpt 1,2, and 3 of Stekel, Read Chpt 1 of
Gentlemen et . al.)
Jan.
29, 2008
Introduction to Microarrays (Read Chpt. 4 and 5
of Stekel, Read Chpt. 2, 3, and 4 of Gentlemen et. al.)
Feb.
5, 2008
Data
Cleansing and Preprocessing (HW 1 Handed
Out)
Feb.
12, 2008
Data
Cleansing and Preprocessing (Read Chpt. 6 of Stekel,
Read Chpt. 11 and 12 of Gentlemen et al.)
Feb.
19, 2008
Statistical
Analysis Overview and Distance Measures (Read
Chpt. 7 of Stekel, Read Chpt. 14 of Gentlemen, Student
Project Plan Due, Student Paper Choice Due, HW 1 Due)
Feb.
26, 2008
Methods
for defining and determining significant levels of differential expression
Mar.
4, 2008
Dimensionality
Reduction(Read
Chpt. 8 of Stekel, Read Chpt. 13, of Gentlemen et
al., HW 2 Handed Out)
Mar.
11, 2008
No
Classes Spring Break
Mar.
18. 2008
Clustering (Read Chpt. 9 of Stekel, Read Chpt.
16 of Gentlemen et. al.)
Mar.
25, 2008
Discriminant
Analysis (Read Chpt. 19, 20, 21, and 22 of
Gentlemen et al.)
April
1, 2008
Network
Analysis (HW 2 Due)
April 8, 2008
Resources
for obtaining meaningful annotation of genes
Browser-based
annotation
April
15, 2008
In
Class Workday for Paper Presentation and
Projects
April
22, 2008
Student
Paper Presentations (Paper presentations due by midnight 4/20/08)
April
29, 2008
Student
Project Presentations (Project presentations due by midnight 4/27/08)
May
13, 2008
No
Final Exam Given All Late Assignments Due