ArticleMolecular systems biology2021
CODEX, a neural network approach to explore signaling dynamics landscapes.
Article in Molecular systems biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 24 citations in OpenAlex.
- Mathematical and Computational Models of Biochemical Reactions and Cell Signaling-From Ordinary Differential Equations to Machine Learning.International journal of molecular sciences · 2026Review
- A Constellation of Fluorescent Biosensors to Illuminate the Galaxy of Protein Kinases.Chembiochem : a European journal of chemical biology · 2026Review
- Progress and new challenges in image-based profiling.Molecular systems biology · 2026Review
- Decoding lysophosphatidic acid signaling in physiology and disease: mapping the multimodal and multinodal signaling networks.Signal transduction and targeted therapy · 2025Review
- Time, the final frontier.Molecular oncology · 2025Article
- A Kolmogorov metric embedding for live cell microscopy signaling patterns.Bioinformatics advances · 2025Article
- Mathematical Modeling and Inference of Epidermal Growth Factor-Induced Mitogen-Activated Protein Kinase Cell Signaling Pathways.International journal of molecular sciences · 2024Review
- Getting real about synthetic data ethics : Are AI ethics principles a good starting point for synthetic data ethics?EMBO reports · 2024Article
- Machine learning inference of continuous single-cell state transitions during myoblast differentiation and fusion.Molecular systems biology · 2024Article
- DynProfiler: a Python package for comprehensive analysis and interpretation of signaling dynamics leveraged by deep learning techniques.Bioinformatics advances · 2024Article
- A guide to ERK dynamics, part 1: mechanisms and models.The Biochemical journal · 2023Article
- Morphodynamical cell state description via live-cell imaging trajectory embedding.Communications biology · 2023Article
- Quantifying the phenotypic information in mRNA abundance.Molecular systems biology · 2022Article
- Optogenetic actuator - ERK biosensor circuits identify MAPK network nodes that shape ERK dynamics.Molecular systems biology · 2022Article
- Signalling dynamics, cell decisions, and homeostatic control in health and disease.Current opinion in cell biology · 2022Review
- Modeling and Simulation of Cell Signaling Networks for Subsequent Analytics Processes Using Big Data and Machine Learning.Bioinformatics and biology insights · 2022Article
- Imaging developmental cell cycles.Biophysical journal · 2021Review
- Data science in cell imaging.Journal of cell science · 2021Review
- CODEX, a neural network approach to explore signaling dynamics landscapes.Molecular systems biology · 2021Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Current studies of cell signaling dynamics that use live cell fluorescent biosensors routinely yield thousands of single-cell, heterogeneous, multi-dimensional trajectories. Typically, the extraction of relevant information from time series data relies on predefined, human-interpretable features. Without a priori knowledge of the system, the predefined features may fail to cover the entire spectrum of dynamics. Here we present CODEX, a data-driven approach based on convolutional neural networks (CNNs) that identifies patterns in time series. It does not require a priori information about the biological system and the insights into the data are built through explanations of the CNNs' predictions. CODEX provides several views of the data: visualization of all the single-cell trajectories in a low-dimensional space, identification of prototypic trajectories, and extraction of distinctive motifs. We demonstrate how CODEX can provide new insights into ERK and Akt signaling in response to various growth factors, and we recapitulate findings in p53 and TGFβ-SMAD2 signaling.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.