Name
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/s11047-010-9200-6 | Natural Computing |
Keywords | Field | DocType |
MP systems,Modeling,Non photochemical quenching,NPQ,Pipeline,Data analysis,Stepwise regression,Neural networks,Optimization,Variable selection,Mitotic cycle,Log-gain,Model validation | Residual,Mitotic cycle,Regression,Feature selection,Computer science,Artificial intelligence,Artificial neural network,Workflow,Machine learning,P system | Journal |
Volume | Issue | ISSN |
10 | 1 | 1567-7818 |
Citations | PageRank | References |
8 | 0.85 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alberto Castellini | 1 | 60 | 14.16 |
| Giuditta Franco | 2 | 136 | 18.34 |
| Roberto Pagliarini | 3 | 35 | 4.69 |