ArticlePLoS computational biology2021
Modeling CRISPR gene drives for suppression of invasive rodents using a supervised machine learning framework.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed, 47 citations in OpenAlex.
- Harnessing CRISPR-Cas technology for insect pest control: current advances and future perspectives.Molecular biology reports · 2026Review
- A simulation-based deep learning framework for spatially explicit malaria modeling of CRISPR suppression gene drive mosquitoes.iScience · 2026Article
- Mapping Gene Drive Dynamics onto Mendelian Models.bioRxiv : the preprint server for biology · 2026Article
- Gaussian process emulation for exploring complex infectious disease models.PLoS computational biology · 2025Article
- SimHumanity: Using SLiM 5.0 to run whole-genome simulations of human evolution.bioRxiv : the preprint server for biology · 2025Article
- Gaussian Process Emulation for Exploring Complex Infectious Disease Models.medRxiv : the preprint server for health sciences · 2025Article
- Maximising Eradication Potential of Rat Gene Drives Using a Two-Target Homing Rescue Strategy: Spatial Modelling of Empirical Data.Molecular ecology · 2025Article
- Population Genetics Meets Ecology: A Guide to Individual-Based Simulations in Continuous Landscapes.Ecology and evolution · 2025Article
- Resource-explicit interactions in spatial population models.Methods in ecology and evolution · 2024Article
- Improving the suppressive power of homing gene drive by co-targeting a distant-site female fertility gene.Nature communications · 2024Article
- Population dynamics in spatial suppression gene drive models and the effect of resistance, density dependence, and life history.bioRxiv : the preprint server for biology · 2024Article
- Performance characteristics allow for confinement of a CRISPR toxin-antidote gene drive for population suppression in a reaction-diffusion model.Proceedings. Biological sciences · 2024Article
- Modelling Emergence ofbioRxiv : the preprint server for biology · 2023Article
- Modeling emergence ofFrontiers in microbiology · 2023Article
- Leveraging a natural murine meiotic drive to suppress invasive populations.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Article
- Stochastic models of Mendelian and reverse transcriptional inheritance in state-structured cancer populations.Scientific reports · 2022Article
- Modelling homing suppression gene drive in haplodiploid organisms.Proceedings. Biological sciences · 2022Article
- Gene drives for vertebrate pest control: Realistic spatial modelling of eradication probabilities and times for island mouse populations.Molecular ecology · 2022Article
- The Challenges in Developing Efficient and Robust Synthetic Homing Endonuclease Gene Drives.Frontiers in bioengineering and biotechnology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 3 countries.
Funding
Abstract
Invasive rodent populations pose a threat to biodiversity across the globe. When confronted with these invaders, native species that evolved independently are often defenseless. CRISPR gene drive systems could provide a solution to this problem by spreading transgenes among invaders that induce population collapse, and could be deployed even where traditional control methods are impractical or prohibitively expensive. Here, we develop a high-fidelity model of an island population of invasive rodents that includes three types of suppression gene drive systems. The individual-based model is spatially explicit, allows for overlapping generations and a fluctuating population size, and includes variables for drive fitness, efficiency, resistance allele formation rate, as well as a variety of ecological parameters. The computational burden of evaluating a model with such a high number of parameters presents a substantial barrier to a comprehensive understanding of its outcome space. We therefore accompany our population model with a meta-model that utilizes supervised machine learning to approximate the outcome space of the underlying model with a high degree of accuracy. This enables us to conduct an exhaustive inquiry of the population model, including variance-based sensitivity analyses using tens of millions of evaluations. Our results suggest that sufficiently capable gene drive systems have the potential to eliminate island populations of rodents under a wide range of demographic assumptions, though only if resistance can be kept to a minimal level. This study highlights the power of supervised machine learning to identify the key parameters and processes that determine the population dynamics of a complex evolutionary system.
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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.