ArticleCell reports methods2023
Embracing enzyme promiscuity with activity-based compressed biosensing.
Article in Cell reports methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
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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
4 citing papers in PubMed, 5 citations in OpenAlex.
- A Novel Unsupervised Learning Model with Bayesian Hyperparameter Optimization for Predicting Substrates of Promiscuous Enzymes.ACS omega · 2026Article
- AND-gated protease-activated nanosensors for programmable detection of anti-tumour immunity.Nature nanotechnology · 2025Article
- Description of an activity-based enzyme biosensor for lung cancer detection.Communications medicine · 2024Article
- Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
The development of protease-activatable drugs and diagnostics requires identifying substrates specific to individual proteases. However, this process becomes increasingly difficult as the number of target proteases increases because most substrates are promiscuously cleaved by multiple proteases. We introduce a method-substrate libraries for compressed sensing of enzymes (SLICE)-for selecting libraries of promiscuous substrates that classify protease mixtures (1) without deconvolution of compressed signals and (2) without highly specific substrates. SLICE ranks substrate libraries using a compression score (
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Registered trials
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