CODEX, a neural network approach to explore signaling dynamics landscapes

Published: 1 February 2021| Version 2 | DOI: 10.17632/4vnndy59fp.2
Maciej Dobrzynski


Supplementary data and R/Python code required to reproduce the figures from the accompanying publication: Jacques et al. "CODEX, a neural network approach to explore signaling dynamics landscapes". The pre-print available here: Included datasets: * Single-cell ERK/Akt activity dynamics in responses to GF treatment. Acquired in-house by Paolo Gagliardi. * p53 responses to ionizing radiation. Data kindly provided by Galit Lahav and Jacob Ornstein-Stewart. * SMAD2 response to TGFb. Data kindly provided by Alexander Loewer. * Drosophila speed movement. Data obtained from * Synthetic data


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Universitat Bern


Molecular Biology, Machine Learning, Clustering, Fluorescence Microscopy, Pattern Recognition in Bioinformatics, Time Series, Computational Biology