2005 Summer Graduate Program
This year the program will focus on Microarray Gene Expression Data Analysis. The program leaders are Shili Lin and Joseph Verducci. The first week is spent in a tutorial, which combines morning lectures with active learning laboratories in the afternoon. The following two weeks are spent working on guided team projects and participating in a mini-conference to share project results. The program is meant primarily for graduate students; college instructors and qualified undergraduates will also be considered.
The 2005 Summer Program dates are August 1 - 19.
Mentors
- Statistics Mentors: Shili Lin and Joe Verducci
- Computational Mentors: Victor Jin, Greg Singer, and Ramana Davuluri
- Wet Lab Leaders: Pearlly Yan, Michael Chan, and Alfred Cheng
Week 1 |
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| Monday, August 1 | |||
| 9:00-12:00pm | Introductory statistics - PPT | ||
| 2:00-4:00pm | Introduction to genetics, molecular biology, microarray technology, and epigenetics (GMBME) - PDF | ||
| Tuesday, August 2 | |||
| 9:00-11:00am | Image analysis and normalization - PDF | ||
| 1:00-3:00pm | Introduction to Bioconductor and R - PPT | ||
| 3:30-5:00pm | Lab visit | Wednesday, August 3 | |
| 9:00-12:00pm | Identification of differentially expressed genes (including demo/lab using Bioconductor) - PDF | ||
| 2:00-3:00pm | GMBME - continued | Thursday, August 4 | |
| 9:00-12:00pm | Cluster of gene expression data (including demo/lab using Bioconductor). Class discovery and classification based on gene expression profile - PDF | ||
| 2:00-3:30pm | Lab visit | Friday, August 5 | |
| 9:00-12:00pm | Description of the projects | ||
| 2:00-3:30pm | GMBME - continued | ||
Team Projects: Monday, August 8 - Wednesday, August 17
Mini-Conference: Thursday, August 18 - Friday, August 19
Project 1: Image analysis and normalization (cDNA array data)
Project Leader: Bertram Zinner
Abstract: Worddoc
Presentation: PPT
In this project, the participants will work on quantifying gene expression levels from fluorescent intensities measured on microarray hybridization experiments. After the image analysis, additional work will be carried out to normalize the data to eliminate systematic biases.
Project 2: Identification of differentially expressed genes
Project Leader: Zailong Wang
Abstract: Worddoc
Presentation: PPT
The goal of this project is to identify the set of genes that are differentially expressed under different settings, for example, under different disease status/stages or different experimental conditions.
Project 3: Cluster analysis of gene expression data
Project Leader: Jin Zhou
Abstract: Worddoc
Presentation: PPT
This project will involve grouping genes according to their "similarities", such as similar expression patterns under several experimental conditions or several time points in a cell cycle.
Project 4: Class discovery and prediction of tumor subtypes
Project Leader: Nusrat Rabbee
Abstract: Worddoc
Presentation: PPT
This project allows the team to explore different statistical methods for tumor subtype classification based on tissue specific gene expression profiles of tumorous samples.
Project 5: Use of ChIP-on-chip to interrogate cancer epigenome
Project Leaders: Victor Jin and Alfred Cheng
Abstract: Worddoc PPT
Presentation: PPT
The modification of chromatin immunoprecipitation (ChIP) to allow analysis on microarray (ChIP-on-chip) represents a genome-wide approach to investigate interactions between proteins and DNA. In this workshop, we will introduce the use of this novel technique to interrogate cancer epigenome such as profiling of histone modifications.
