DIMACS Short Course: Gene Expression Resources at the National Center for Biotechnology Information (NCBI)
Speaker: Susan M. Dombrowski, Ph.D., NCBI
April 13 - 14, 2004
DIMACS Center, CoRE Building, Rutgers University
- Organizers:
- Paul Ehrlich, BIOMAPS Institute, pehrlich@biomaps.rutgers.edu
- Mel Janowitz, DIMACS, melj@dimacs.rutgers.edu
- Tara Matise, Department of Genetics, matise@biology.rutgers.edu
Presented by The National Center for Biotechnology Information, the
Department of Genetics at Rutgers University,
the DIMACS Special Focus
on Computational Molecular Biology and the BIOMAPS Institute for
Quantitative Biology.
Intended Audience
This course is intended for principal investigators, senior scientists, thesis directors, laboratory directors, postdoctoral fellows, graduate students, advanced undergraduates and scientific support staff who would like to incorporate gene expression data into their research.
Course Summary and Objectives
The training course presented by the NCBI is a 1 ½ hour lecture and a 2 hour computer workshop that demonstrates how the gene expression resources and tools available at the NCBI can be used to obtain qualitative and quantitative measurements of gene expression in different biological samples and under various experimental conditions
In this course, workshop participants will learn how to:
- Query the Gene Expression Omnibus (GEO) database and the two
related Entrez databases, GEO Expressions and GEO DataSets to:
- identify genes that may be regulated together and be part of a common regulatory pathway (profile neighbors);
- use sequence similarity searching to find expression
patterns for genes which may be members of a multi-gene family
(sequence neighbors);
- perform cross-species comparisons of expressed genes.
- Use the Digital Differential Display tool for the comparative analysis of mRNA abundance in cDNA (EST) libraries;
- Use the xProfiler tool to measure mRNA abundance in SAGE libraries;
- Mine the data in the Online Mendelian Inheritance in Man (OMIM)
database and NCBI's variation database, dbSNP, to find polymorphisms
that may alter gene expression;
- Integrate and visualize expression-related data (UniGene, SAGE
tags, CpG islands and variation) in NCBI's genome browser, MapViewer.
Attendance at the lecture is a prerequisite for participation in the
computer session.
For further information on Geo see: http://www.ncbi.nlm.nih.gov/geo/
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Document last modified on February 12, 2004.