Literature DB >> 19441879

Modeling and managing experimental data using FuGE.

Andrew R Jones1, Allyson L Lister, Leandro Hermida, Peter Wilkinson, Martin Eisenacher, Khalid Belhajjame, Frank Gibson, Phil Lord, Matthew Pocock, Heiko Rosenfelder, Javier Santoyo-Lopez, Anil Wipat, Norman W Paton.   

Abstract

The Functional Genomics Experiment data model (FuGE) has been developed to increase the consistency and efficiency of experimental data modeling in the life sciences, and it has been adopted by a number of high-profile standardization organizations. FuGE can be used: (1) directly, whereby generic modeling constructs are used to represent concepts from specific experimental activities; or (2) as a framework within which method-specific models can be developed. FuGE is both rich and flexible, providing a considerable number of modeling constructs, which can be used in a range of different ways. However, such richness and flexibility also mean that modelers and application developers have choices to make when applying FuGE in a given context. This paper captures emerging best practice in the use of FuGE in the light of the experience of several groups by: (1) proposing guidelines for the use and extension of the FuGE data model; (2) presenting design patterns that reflect recurring requirements in experimental data modeling; and (3) describing a community software tool kit (STK) that supports application development using FuGE. We anticipate that these guidelines will encourage consistent usage of FuGE, and as such, will contribute to the development of convergent data standards in omics research.

Mesh:

Year:  2009        PMID: 19441879     DOI: 10.1089/omi.2008.0080

Source DB:  PubMed          Journal:  OMICS        ISSN: 1536-2310


  2 in total

1.  The gel electrophoresis markup language (GelML) from the Proteomics Standards Initiative.

Authors:  Frank Gibson; Christine Hoogland; Salvador Martinez-Bartolomé; J Alberto Medina-Aunon; Juan Pablo Albar; Gyorgy Babnigg; Anil Wipat; Henning Hermjakob; Jonas S Almeida; Romesh Stanislaus; Norman W Paton; Andrew R Jones
Journal:  Proteomics       Date:  2010-09       Impact factor: 3.984

2.  LabTrove: a lightweight, web based, laboratory "blog" as a route towards a marked up record of work in a bioscience research laboratory.

Authors:  Andrew J Milsted; Jennifer R Hale; Jeremy G Frey; Cameron Neylon
Journal:  PLoS One       Date:  2013-07-23       Impact factor: 3.240

  2 in total

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