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Statistical Bioinformatics Group
University of Virginia
,
Charlottesville, VA
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Statistical Bioinformatics in Medicine (PHS795, Fall 2009)
'09 Course syllabus
Project guideline and references
Potential Project Topics
Final Project Evaluation Sheet
Lecture Notes (L: regular, S: special topic lectures):
L1.
Introduction
L3.
Quality control and statistical assement on large screening data
L4.
Statistical control and tests for multiple comparisons in high throughput data
L5.
Unsupervised Learning
;
Cluster Image Map Demo
;
Sequence Similarity Demo
L6.
Supervised Learning and Misclassification Penalized Posterior (MIPP)
L10.
Statistical Resampling (Monte Carlo, EM, Bootstrapping, MCMC)
L7.
Multi-Dimensional Visualization
L9.
Experimental design in high throughput biological experiments
L11.
Boolean and Bayesian Belief Gene Network Modeling
L12.
Machine Learning: Neural Network and Genetic Algorithms
S1.
Human genome project and microarray & mass spectrometry technology
S2.
R and Bioconductor packages in bioinformatics
(Invited Tutorial by Dr. Sang-Hoon Cho)
S3.
The Clinical Data Repository at the University of Virginia
(Invited Lecture by Dr. Jason Lyman)
S4.
High Throughput Sequencing Data and Analysis
(Invited Lecture by Dr. Stefan Bekiranov)
S5.
Genome-Wide Association Study
(Invited Lecture by Dr. Ming Li)
Course R Code
Example Microarray Dataset
Example Proteomics Data
Example Nonlinear Data
