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These Python scripts define and simulate the translational coincidence model. This model takes measured transcript dynamics (Blasing et al, 2005) in 12L:12D, measured synthesis rates of protein in light compared to dark (Pal et al, 2013), and outputs predicted changes in protein abundance between short (6h) and long (18h) photoperiods. These are compared to the photoperiod proteomics dataset we generated.

Submitter: Daniel Seaton

Biological problem addressed: Model Analysis Type

Investigation: Photoperiodic control of the Arabidopsis proteo...

Study: Modelling and analysis of translational coincid...

Organisms: Arabidopsis thaliana : Col-0 wild type (wild-type / wild-type)

Models: Translational coincidence modelling - python sc...

SOPs: No SOPs

Data files: Blasing et al, 2005, diurnal microarray dataset..., Table EV1 - Quantitative proteomics dataset

Snapshots: No snapshots

Created: 4th Dec 2017 at 21:41, Last updated: 20th Feb 2018 at 22:03