ArticleAnalytical chemistry2022
A Bayesian Approach to Extracting Kinetic Information from Artificial Enzymatic Networks.
Article in Analytical chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Timed batch inputs unlock substantially higher yields for enzymatic cascades.Nature chemistry · 2026Article
- Changes in the pH-Activity Profiles of Enzymes upon Immobilization on Polyelectrolyte-Containing Hydrogels.Chem & bio engineering · 2026Article
- A recursive enzymatic competition network capable of multitask molecular information processing.Nature chemistry · 2026Article
- Molecular systems engineering of synthetic cells.Nature chemistry · 2026Review
- Quantitative Online Monitoring of an Immobilized Enzymatic Network by Ion Mobility-Mass Spectrometry.Journal of the American Chemical Society · 2024Article
- Highly parallel and ultra-low-power probabilistic reasoning with programmable gaussian-like memory transistors.Nature communications · 2024Article
- Exploring Emergent Properties in Enzymatic Reaction Networks: Design and Control of Dynamic Functional Systems.Chemical reviews · 2024Review
- Iterative design of training data to control intricate enzymatic reaction networks.Nature communications · 2024Article
- Computing Arithmetic Functions Using Immobilised Enzymatic Reaction Networks.Angewandte Chemie (International ed. in English) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In order to create artificial enzymatic networks capable of increasingly complex behavior, an improved methodology in understanding and controlling the kinetics of these networks is needed. Here, we introduce a Bayesian analysis method allowing for the accurate inference of enzyme kinetic parameters and determination of most likely reaction mechanisms, by combining data from different experiments and network topologies in a single probabilistic analysis framework. This Bayesian approach explicitly allows us to continuously improve our parameter estimates and behavior predictions by iteratively adding new data to our models, while automatically taking into account uncertainties introduced by the experimental setups or the chemical processes in general. We demonstrate the potential of this approach by characterizing systems of enzymes compartmentalized in beads inside flow reactors. The methods we introduce here provide a new approach to the design of increasingly complex artificial enzymatic networks, making the design of such networks more efficient, and robust against the accumulation of experimental errors.
Indexed as
Identifiers
What OpenQuestion holds
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.