A proposed framework for the description of plant metabolomics experiments and their results.
The study of the metabolite complement of biological samples, known as metabolomics, is creating large amounts of data, and support for handling these data sets is required to facilitate meaningful analyses that will answer biological questions. We present a data model for plant metabolomics known as ArMet (architecture for metabolomics). It encompasses the entire experimental time line from experiment definition and description of biological source material, through sample growth and preparation to the results of chemical analysis. Such formal data descriptions, which specify the full experimental context, enable principled comparison of data sets, allow proper interpretation of experimental results, permit the repetition of experiments and provide a basis for the design of systems for data storage and transmission. The current design and example implementations are freely available (http://www.armet.org/). We seek to advance discussion and community adoption of a standard for metabolomics, which would promote principled collection, storage and transmission of experiment data.
Jenkins
Helen
H
Department of Computer Science, University of Wales, Penglais, Aberystwyth, Ceredigion, Wales, UK.
Hardy
Nigel
N
Beckmann
Manfred
M
Draper
John
J
Smith
Aileen R
AR
Taylor
Janet
J
Fiehn
Oliver
O
Goodacre
Royston
R
Bino
Raoul J
RJ
Hall
Robert
R
Kopka
Joachim
J
Lane
Geoffrey A
GA
Lange
B Markus
BM
Liu
Jang R
JR
Mendes
Pedro
P
Nikolau
Basil J
BJ
Oliver
Stephen G
SG
Paton
Norman W
NW
Rhee
Sue
S
Roessner-Tunali
Ute
U
Saito
Kazuki
K
Smedsgaard
Jørn
J
Sumner
Lloyd W
LW
Wang
Trevor
T
Walsh
Sean
S
Wurtele
Eve Syrkin
ES
Kell
Douglas B
DB
D003628:Database Management Systems; D016208:Databases, Factual / Q000592:standards*; D004282:Documentation / Q000379:methods* / Q000592:standards; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D010944:Plants / Q000378:metabolism*; D020543:Proteome / Q000378:metabolism*; D040901:Proteomics / Q000379:methods / Q000592:standards; D012106:Research / Q000592:standards; D012107:Research Design; D012984:Software; D014584:User-Computer Interface
D020543:Proteome