bioinfworkshop.html

Workshop on Bioinformatics
December 27-28, 2004
Hyderabad, India

In conjunction with
International Conference on the
FUTURE OF STATISTICAL THEORY, PRACTICE AND EDUCATION
(Dec. 29 -Jan 1, 2005)

Cosponsor: Centre for Cellular & Molecular Biology (CCMB)
www.ccmb.res.in

Organizers

Shyamal Peddada, National Institute of Environmental Health Sciences (NIH), USA
Mei-Ling Ting Lee, Harvard University, USA
K. Guruprasad, Bioinformatics Division, CCMB, Hyderabad

This workshop is intended for researchers and graduate students interested in the design and analysis of gene expression microarray experiments and in gene sequence and network analysis. A wide range of topics will be discussed at various levels of complexity and understanding. However, as far as possible, technical details will be kept at the very minimum so that the workshop is accessible to a broad audience.

The list of topics include:

Introduction to microarray data: A basic understanding of microarray data, different sources of variation and bias in microarray data, background noise, normalization methods, data transformation.

Design and analysis: Experimental designs for conducting microarray experiments, different methods of analyses such as ANOVA based methods, order restricted inference based method for time course and dose response experiments, permutation and bootstrap procedures, Bayes and empirical Bayes procedures.

Cluster and Descriminant analysis: Principal component analysis, singular value decomposition, self organizing maps, discrimination and classification, neural networks, support vector machines, CART, Random Forests, etc.

Sequence analysis and Regulatory Networks: HPII techniques for genome sequences and data management, introduction to gene regulatory and cellular networks, signal transduction in cellular networks, introduction to techniques for modeling and simulation of regulatory networks, methods for sequence alignments.

List of speakers:

Dr. Sudeshna Adak, GE India Technology Center, Bangalore
Ranajit Chakraborty, U. Cincinnati, USA
Dr. Francesca Chiaromonte, Penn State University, USA
Dr. Probal Chaudhuri, Indian Statistical Institute, India
Mr. Jagir Hussan, IBM, India
Dr. Babu Narayanan, GE, India
Dr. Shyamal Peddada, National Institute of Environmental Health Sciences (NIH), USA
Dr. Sunil Rao, Case Western Reserve University, USA

Day 1: December 27, 2004

Introduction

What is Bioinformtics: Old Wine in a New Bottle? (Ranajit Chakraborty)

Session #1: 1hr, 30 minutes
Genome Probing Using Microarrays (lecturer: Babu Narayanan)

1. DNA, RNA, Proteins, and Gene Expression
2. Microarray Technology
3. Inherent Variability in microarray Data
4. Missing Values and Saturated Intensity Readings
5. Background Noise, Transformation and Normalization

Session #2: 1hr
Statistical Models (lecturer: Sunil Rao)

1. Multiple Testing in Microarray Studies
2. Permutation Tests in Microarray Data
3. The false discovery rate

***** Lunch: 12:00 noon to 1:00 pm

Session #2 (continued): 1hr

Session #3: 1hr
Unsupervised Exploratory Analysis (lecturer: Probal Chaudhuri)

1. Cluster Analysis
2. Principal Components and Singular Value Decomposition
3. Self-organizing Maps

***** Coffee break: 30 minutes

Session #3 (continued): 1hr

Session # 4: 1hr
Comparison of Oligonucleotide Microarray Platforms (lecturer: Sudeshna Adak)

1. Overview of Oligonucleotide microarrays
- Chip Fabrication: How it is different from cDNA arrays

2. Comparison of Chip Designs
- Available Platforms: Design differences in Affymetrix,
Agilent and Amersham Oligonucleotide chips

3. Comparison of Differences in Experimental Data
        - Design of cross-platform experiments
        - Analysis of cross-platform experiments
        - Comparison of cross-platform performance

4. Advantages/Disadvantages of Oligonucleotide platforms.

Day 2: December 28, 2004

Session #5: 1hr, 30 minutes
Supervised Learning Methods

1. Discrimination and Classification (lecturer: Francesca Chiaromonte)
2. Artificial Neural Networks and Machine Learning (lecturer: Probal Chaudhuri)
3. Support Vector Machines, Bootstrap, CART, Random Forests

***** Coffee break: 30 minutes

Session #6: 1hr
Analysis of time-course and dose-response microarray experiments
(Lecturer: Shyamal Peddada)

1. Introduction
    - Types of data
    - An example
    - The problem of interest
2. An overview of various methods
    - Correlation based methodology
    - Confidence interval based methodology
    - GA/KNN methodology
    - Order restricted inference based methodology
3. Order restricted inference (ORI) approach
    - Introduction to ORI
    - The ORI methodology for gene selection and clustering
4. Case study: Analysis of MCF-7 Breast cancer cell line data.
5. Concluding remarks.

***** Lunch: 12:00 noon to 1:00 pm.

Session #6 (continued): 1hr

Session #7: 1hr, 30 minutes
Bayesian methods for microarray data (Lecturer: Sunil Rao)

1. The False Discovery Rate (cont'd)
2. Bayesian Variable Selection

***** Coffee break: 30 minutes

Session #8: 1hr, 30 minutes
Sequence Processing and Regulatory Networks (Lecturer: Jagir Hussan)

1.High Performance Information Infrastructure (HPII) for Genome Sequences
    Introduction to HPII techniques, including
        - Data partitioning methods
        - Instruction partitioning methods
        - Dedicated hardware based methods
        - Knowledge based organization methods
    A sample bioinformatic application (Virus identification, SARS etc) that requires HPII

2. Gene Regulatory Networks
        Introduction to Gene Regulatory networks
        Introduction to Cellular Networks (Optional)
        Introduction to Signal transduction in cellular networks
        Introduction to gene expression data to network identification
        - Brief on Reverse engineering regulatory networks from gene expression data
        - Gene knock-out based reconstruction techniques
        - Modeling and Simulation of regulatory networks
        Brief on Phenotype to network correlation studies (Optional)

update: Nov. 30, 2004