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Data analysis pipeline from laboratory to MP models

Alberto Castellini
•
Giuditta Franco
•
Roberto Pagliarini
2011
  • journal article

Periodico
NATURAL COMPUTING
Abstract
A workflow for data analysis is introduced to synthesize flux regulation maps of a Metabolic P system from time series of data observed in laboratory. The procedure is successfully tested on a significant case study, the photosynthetic phenomenon called NPQ, which determines plant accommodation to environmental light. A previously introduced MP model of such a photosynthetic process has been improved, by providing an MP system with a simpler regulative network that reproduces the observed behaviors of the natural system. Two regression techniques were employed to find out the regulation maps, and interesting experimental results came out in the context of their residual analysis for model validation.
DOI
10.1007/s11047-010-9200-6
WOS
WOS:000288255800005
Archivio
https://hdl.handle.net/11390/1246529
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-79952756346
https://ricerca.unityfvg.it/handle/11390/1246529
Diritti
metadata only access
Soggetti
  • MP system

  • Modeling

  • Non photochemical que...

  • NPQ

  • Pipeline

  • Data analysi

  • Stepwise regression

  • Neural network

  • Optimization

  • Variable selection

  • Mitotic cycle

  • Log-gain

  • Model validation

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