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Embracing Dynamic Models for Gene Drive Management.
Golnar, Andrew J; Ruell, Emily; Lloyd, Alun L; Pepin, Kim M.
Affiliation
  • Golnar AJ; National Wildlife Research Center, United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, 4101 Laporte Ave., Fort Collins, CO 80521, USA. Electronic address: andrew.golnar@usda.gov.
  • Ruell E; National Wildlife Research Center, United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, 4101 Laporte Ave., Fort Collins, CO 80521, USA.
  • Lloyd AL; Biomathematics Graduate Program and Department of Mathematics, North Carolina State University, Raleigh, NC 27695, USA.
  • Pepin KM; National Wildlife Research Center, United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, 4101 Laporte Ave., Fort Collins, CO 80521, USA.
Trends Biotechnol ; 39(3): 211-214, 2021 03.
Article in En | MEDLINE | ID: mdl-33010965
ABSTRACT
Robust methods of predicting how gene drive systems will interact with ecosystems is essential for safe deployment of gene drive technology. We describe how quantitative tools can reduce risk uncertainty, streamline empirical research, guide risk management, and promote cross-sector collaboration throughout the process of gene drive technology development and implementation.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Ecosystem / Gene Drive Technology / Models, Genetic Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Trends Biotechnol Year: 2021 Document type: Article
Fulltext
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Ecosystem / Gene Drive Technology / Models, Genetic Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Trends Biotechnol Year: 2021 Document type: Article