ArticlePlant physiology2005
Toward supportive data collection tools for plant metabolomics.
Article in Plant physiology, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- MeRy-B: a web knowledgebase for the storage, visualization, analysis and annotation of plant NMR metabolomic profiles.BMC plant biology · 2011Article
- Data standards for Omics data: the basis of data sharing and reuse.Methods in molecular biology (Clifton, N.J.) · 2011Review
- Enhancement of plant metabolite fingerprinting by machine learning.Plant physiology · 2010Article
- Recent Advances in Medicago truncatula Genomics.International journal of plant genomics · 2008Article
- Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI).Metabolomics : Official journal of the Metabolomic Society · 2007Article
- Purdue ionomics information management system. An integrated functional genomics platform.Plant physiology · 2007Article
- Biological databases for plant research.Plant physiology · 2005Article
- Standard reporting requirements for biological samples in metabolomics experiments: microbial and in vitro biology experiments.Metabolomics : Official journal of the Metabolomic SocietyArticle
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Over recent years, a number of initiatives have proposed standard reporting guidelines for functional genomics experiments. Associated with these are data models that may be used as the basis of the design of software tools that store and transmit experiment data in standard formats. Central to the success of such data handling tools is their usability. Successful data handling tools are expected to yield benefits in time saving and in quality assurance. Here, we describe the collection of datasets that conform to the recently proposed data model for plant metabolomics known as ArMet (architecture for metabolomics) and illustrate a number of approaches to robust data collection that have been developed in collaboration between software engineers and biologists. These examples also serve to validate ArMet from the data collection perspective by demonstrating that a range of software tools, supporting data recording and data upload to central databases, can be built using the data model as the basis of their design.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.