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Statistical  Methods in Bioinformatics:   Case Studies

Schedule:

Sep 14 (Lecture 1):  Dr. Ru-Fang Yeh:

Overview of statistical issues in bioinformatics. Introduction to  microarray analysis;

slides

Sep 21 (Lecture 2): Dr. Ru-Fang Yeh:
Clustering; Tiling array analysis: ChIP-chip for histone modifications in tumors.

slides

Sep 28 (Lecture 3): Dr. Yuan-Yuan Xiao
 Exploration and analysis of Affymetrix SNP arrays

slides

 Oct 5 (Lecture 4): Dr. Jane Fridlyand
 Copy number arrays and example of  meta-analysis of genomic data:
 Demonstration of the methodology on the breast cancer data;

slides

 Oct 12 (Lecture 5): Dr. Jane Fridlyand
  Data Integration (continiued) and Classification in genomics: Application to tumor data; 

slides

 Oct 19 (Lecture 6): Dr. Mark Segal
 Validation in genomics: CpG island methylation revisited;

slides

Oct 26 (Lecture 7): Drs. Mark Segal & Yuan-Yuan Xiao
E-values for protein database searches based on tandem mass spectrometry scoring;

slides

Challenges in mass-spectrometry data analysis;

slides

Nov 2 (Lecture 8): Dr. Haiyan Huang, UC Berkeley
A statistical framework to infer functional gene associations from multiple biologically
interrelated microarray experiments: application to yeast and human data;

Nov 9 (Lecture 9): Dr. Imola Fodor, LLNL
Phenotypic characterization of Yersinia pestis;

Nov 16 (Lecture 10): Dr. Katie Pollard, UC Davis
Detecting lineage-specific evolution of DNA.


Grades: 
  100% - classroom participation

Recommended readings:
  1. The Elements of Statistical Learning by T. Hastie, R. Tibshirani, J. H. Friedman. 2001. Springer.
  2. Bioinformatics and Computational Biology Solutions using R and Bioconductor, edited by R. Gentleman et al. 2005. Springer.
  3. Statistical Analysis of Gene Expression Microarray Data, edited by T.P. Speed. 2003. Chapman & Hall/CRC.
  4. A Primer of Genome Science by G. Gibson & S.V. Muse. 2001. Sinauer Associates.