Commentary

MIAME/Plant – adding value to plant microarrray experiments

Philip Zimmermann¹ , Beatrice Schildknecht² , David Craigon² , Margarita Garcia-Hernandez³ , Wilhelm Gruissem¹ , Sean May² , Gaurab Mukherjee⁴ , Helen Parkinson⁴ , Seung Rhee , Ulrich Wagner¹ and Lars Hennig¹

¹  Swiss Federal Institute of Technology – ETH Zurich, ETH Center, CH-8092 Zurich, Switzerland

²  The Nottingham Arabidopsis Stock Center (NASC), Division of Plant Sciences, University of Nottingham, Sutton Bonington LE12 5RD, UK

³  The Arabidopsis Information Resource (TAIR), Carnegie Institution of Washington, 260 Panama St, Stanford, CA 94305, USA

⁴  European Bioinformatics Institute (EBI), European Bioinformatics Institute, EMBL outstation, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK

author email corresponding author email

Plant Methods 2006, 2:1doi:10.1186/1746-4811-2-1

Published:	9 January 2006

Abstract

Appropriate biological interpretation of microarray data calls for relevant experimental annotation. The widely accepted MIAME guidelines provide a generic, organism-independant standard for minimal information about microarray experiments. In its overall structure, MIAME is very general and specifications cover mostly technical aspects, while relevant organism-specific information useful to understand the underlying experiments is largely missing. If plant biologists want to use results from published microarray experiments, they need detailed information about biological aspects, such as growth conditions, harvesting time or harvested organ(s). Here, we propose MIAME/Plant, a standard describing which biological details to be captured for describing microarray experiments involving plants. We expect that a more detailed and more systematic annotation of microarray experiments will greatly increase the use of transcriptome data sets for the scientific community. The power and value of systematic annotation of microarray data is convincingly demonstrated by data warehouses such as Genevestigator^® or NASCArrays, and better experimental annotation will make these applications even more powerful.