ArticleNature computational science2024
Machine learning-guided engineering of genetically encoded fluorescent calcium indicators.
Article in Nature computational science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed.
- Noninvasive methods to monitor dynamic single-cell events.Trends in cell biology · 2026Review
- Genetically encoded tools for tracking metabolites in live cells.Biochemical Society transactions · 2026Review
- Artificial allosteric protein switches with machine-learning-designed receptors.Nature biotechnology · 2026Article
- Article
- Genetically encoded biosensors enabled high-throughput screening of microbial cell factories.Engineering microbiology · 2026Review
- AI4Protein: transforming the future of protein design.Science China. Life sciences · 2025Review
- Decoding Molecular Network Dynamics in Cells: Advances in Multiplexed Live Imaging of Fluorescent Biosensors.Biosensors · 2025Review
- Biophysics-based protein language models for protein engineering.Nature methods · 2025Article
- Genetically encoded sensors illuminateIBRO neuroscience reports · 2025Article
- Principles and Design of Molecular Tools for Sensing and Perturbing Cell Surface Receptor Activity.Chemical reviews · 2025Review
- Lanthanide-Controlled Protein Switches: Development and In Vitro and In Vivo Applications.Angewandte Chemie (International ed. in English) · 2025Article
- Illuminating anions in biology with genetically encoded fluorescent biosensors.Current opinion in chemical biology · 2025Review
- Calcium Indicators with Fluorescence Lifetime-Based Signal Readout: A Structure-Function Study.International journal of molecular sciences · 2024Article
- Neuromodulator and neuropeptide sensors and probes for precise circuit interrogation in vivo.Science (New York, N.Y.) · 2024Review
- Machine learning-guided engineering of genetically encoded fluorescent calcium indicators.Nature computational science · 2024Article
- Current Status and Future Strategies for Advancing Functional Circuit MappingThe Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
Here we used machine learning to engineer genetically encoded fluorescent indicators, protein-based sensors critical for real-time monitoring of biological activity. We used machine learning to predict the outcomes of sensor mutagenesis by analyzing established libraries that link sensor sequences to functions. Using the GCaMP calcium indicator as a scaffold, we developed an ensemble of three regression models trained on experimentally derived GCaMP mutation libraries. The trained ensemble performed an in silico functional screen on 1,423 novel, uncharacterized GCaMP variants. As a result, we identified the ensemble-derived GCaMP (eGCaMP) variants, eGCaMP and eGCaMP
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Registered trials
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.