Decision support for the comparative evaluation and selection of analytical methods: detection of genetically modified organisms as an example

Autor: Kristina Gruden, Arne Holst-Jensen, David Dobnik, Marko Bohanec, Yves Bertheau, Jana Žel
Přispěvatelé: Dobnik, David, Department of Biotechnology and Systems Biology, National Institute of Biology, Département Santé des Plantes et Environnement (DPT SPE), Institut National de la Recherche Agronomique (INRA), Centre d'Ecologie et des Sciences de la COnservation (CESCO), Muséum national d'Histoire naturelle (MNHN)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Norwegian Veterinary Institute [Oslo], Jozef Stefan Institute [Ljubljana] (IJS), FP6 contract no. 007158 (Project Co-Extra), Slovenian Research Agency (contract number P4-0165), Research Council of Norway, European Project: 613908,EC:FP7:KBBE,FP7-KBBE-2013-7-single-stage,DECATHLON(2013), Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)
Jazyk: angličtina
Rok vydání: 2018
Předmět:
0301 basic medicine
Decision support system
Computer science
detection
Multiple methods
computer.software_genre
01 natural sciences
Applied Microbiology and Biotechnology
Analytical Chemistry
NBT
FP6 research project
Multiplex
Safety
Risk
Reliability and Quality

DSS
evaluation
Vegetal Biology
GMO
Decision Support System
Variety (cybernetics)
méthode de détection
OGM
Genetically modified organism
method
performance
selection
Multicriteria decision analysis
Co-Extra
DeXi
New Breeding Technique
Safety Research
Detection of genetically modified organisms
Machine learning
Comparative evaluation
03 medical and health sciences
[SDV.BV]Life Sciences [q-bio]/Vegetal Biology
Selection (genetic algorithm)
business.industry
010401 analytical chemistry
méthode de quantification
0104 chemical sciences
030104 developmental biology
modèle de décision
plante transgénique
Artificial intelligence
business
computer
Biologie végétale
Food Science
Decision analysis
Zdroj: Food Analytical Methods, 1-18. (2018)
Food Analytical Methods
Food Analytical Methods, 2018, pp.1-18. ⟨10.1007/s12161-018-1194-1⟩
Food Analytical Methods, Springer, 2018, pp.1-18. ⟨10.1007/s12161-018-1194-1⟩
ISSN: 1936-9751
1936-976X
DOI: 10.1007/s12161-018-1194-1⟩
Popis: International audience; The selection of the best-fit-for-purpose analytical method to be implemented in the laboratory is difficult due to availability of multiple methods, targets, aims of detection, and different kinds and sources of more or less reliable information. Several factors, such as method performance, practicability, cost of setup, and running costs need to be considered together with personnel training when selecting the most appropriate method. The aim of our work was to prepare a flexible multicriteria decision analysis model suitable for evaluation and comparison of analytical methods used for the purpose of detecting and/or quantifying genetically modified organisms, and to use this model to evaluate a variety of changing analytical methods. Our study included selection of PCR-, isothermal-, protein-, microarray-, and next-generation sequencing-based methods in simplex and/or multiplex formats. We show that the overall result of their fitness for purpose is relatively similar; however, individual criteria or a group of related criteria exposed more substantial differences between the methods. The proposed model of this decision support system enables easy modifications and is thus suitable for any other application of complex analytical methods.
Databáze: OpenAIRE