Back to search

Article

A simulation-based deep learning framework for spatially explicit malaria modeling of CRISPR suppression gene drive mosquitoes

2025-03-13

Abstract excerpt

Engineered CRISPR gene drives are a promising new strategy for fighting malaria and other vector-borne diseases, made possible by genome engineering with the CRISPR-Cas9 system. One useful approach to predict the outcome of a gene drive mosquito release is individual-based modeling, which can be spatially explicit and allows flexible parameters for drive efficiency, mosquito ecology, and malaria transmission. Howe...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
5629c175-0491-50be-9077-acdc523322f6
DOI
10.1101/2025.03.10.642387
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
A simulation-based deep learning framework for spatially explicit malaria modeling of CRISPR suppression gene drive mosquitoesDOI 10.1101/2025.03.10.642387
MGDrivE: A modular simulation framework for the spread of gene drives through spatially-explicit mosquito populationsSemantic proximity
MGD riv E: A modular simulation framework for the spread of gene drives through spatially explicit mosquito populationsSemantic proximity
MGDrivE 3: A decoupled vector-human framework for epidemiological simulation of mosquito genetic control tools and their surveillanceSemantic proximity
MGDrivE 2: A simulation framework for gene drive systems incorporating seasonality and epidemiological dynamicsSemantic proximity
Simulations reveal high efficiency and confinement of a population suppression CRISPR toxin-antidote gene driveSemantic proximity
MGDrivE 3: A decoupled vector-human framework for epidemiological simulation of mosquito genetic control tools and their surveillanceSemantic proximity
Impact of mosquito gene drive on malaria elimination in a computational model with explicit spatial and temporal dynamicsSemantic proximity
MGDrivE 2: A simulation framework for gene drive systems incorporating seasonality and epidemiological dynamicsSemantic proximity
Current CRISPR gene drive systems are likely to be highly invasive in wild populations.Semantic proximity
Population modification strategies for malaria vector control are uniquely resilient to observed levels of gene drive resistance alleles.Semantic proximity
The potential of gene drive releases in malaria vector species to reduce the malaria burden in different African environmentsSemantic proximity
Engineering resilient gene drives for sustainable malaria control by predicting, testing and overcoming target site resistance in Anopheles gambiae.Semantic proximity
Select a neighboring publication to make it the new centre.