1. NYU Microarray Database (NYUMAD)
Marc Rejali

2. Overview Supports collaborative research Large data sets
Extensible Analysis functionality
Efficient and intuitive interface
Flexible design
Use of standards (MAGE-ML)

3. Architecture/Design Front Tier Middle Tier Back Tier Java Application
Java Applet
Custom
Web Pages
Web pages
Application
Front Tier
Custom Calculation
& clustering Modules
XML ( MAGE-ML)
Local C or C++ modules on user’s computer
HTTP
Clustering Modules
Java Servlets
Middle Tier
C++, C, Java, other languages
Calculation Modules DB
Relational
Files
Back Tier

4. Data Sharing Collaborative Data sharing Controlled visibility/access
group-based read/write access
public/private data
Community access to public data
HTTP communication
XML and MAGE-ML standard
Easy data import/export
Can create customized data sets
Can filter and transform export data

5. Array Definition Screen

6. Experiment/Hybridization Data Screen

7. Data Analysis 1 Clustering analysis Expression profile analysis
Data filtering, normalization, transformation
New ‘shrinkage’ similarity measure
Gene and experiment cluster generation
Graphical display of clustering
Expression profile analysis
Find expression profiles correlated/anti-correlated to a given gene’s expression profile
Compare to a synthetic profile
Data filtering, normalization and transformation available

8. Data Analysis 2 Use of fast plug-in C/C++ analysis modules
Sophisticated new technique for normalization and differential expression

9. Clustering Screen

10. Data Content Experiments Hybridization results Array Design Protocols
calculated and typed experimental factors
templates for factor input
Hybridization results
batch and regular import
Array Design
array feature annotations
User arrays
Protocols

11. Software Engineering
Three-tier architecture ensures performance, scalability and flexibility
Client and Server caching ensure speed
Re-use demonstrated with NYUSIM