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Microarray Informatics

Description: This course focuses on the analysis of data derived from microarray experiments. The courses is divided into four sections that cover the fundamentals of microarrays, the stages of data collection and analysis, the informatics systems required to track and collate data, and the latest software packages.

COURSE OUTLINE

INTRODUCTION
1. Course Information
2. Interface Tour
3. Course Overview

FUNDAMENTALS
4. Objectives
5. Microarray Fundamentals
6. Expression Profiling (ESTs, SAGE, MPSS)
7. Types of Microarrays Experiments
8. Microarrays Limitations
9. Progress Check

ANALYTICS
10. Objectives
11. Overview of Microarray Process
12. Image Analysis
13. Normalization
14. Filtration
15. Pattern Discovery
16. Biological Interpretation
17. Progress Check

INFORMATICS
18. Objectives
19. Information Management Systems
20. LIMs and AIMs
21. Data Aquisition and Analysis Databases
22. Microarray Master Manager
23. Data Standards
24. Progress Check

SOFTWARE
25. Objectives
26. Available Software
27. Example Dataset
28. GeneMaths
29. Spotfire

COURSE OBJECTIVES

Students completing this course should be able to:

List the different types of microarray technologies
Specify at least 5 different applications of microarrays
Explain how microarrays are used for gene expression profiling
List the limitations of microarray for gene expression profiling
Name 3 alternative technologies that can be used for gene expression
Specify the steps of microarray data analysis.
List the issues associated with microarray data analysis
Explain how normalization copes with experimental variability
Explain what filtering is and how it should be properly used
List different pattern discovery techniques such as clustering and Principal Component Analysis
Explain how biological interpretation is linked to pattern discovery
List the different modules of a microarray informatics system
Distinguish between Laboratory Information Management Systems (LIMS) and Analysis Information Management Systems (AIMS)
List the information contained in Data Acquisition and Analysis Databases
List various data standards
Understand how various software packages allow you to analyze data

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