Evolving Improved Sampling Protocols for Dose-Response Modelling Using Genetic Algorithms with a Profile-Likelihood Metric.

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Bibliographic Details
Title: Evolving Improved Sampling Protocols for Dose-Response Modelling Using Genetic Algorithms with a Profile-Likelihood Metric.
Authors: Lam NN; Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand. nicholas.lam@pg.canterbury.ac.nz., Murray R; School of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand., Docherty PD; Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand.; Institute of Technical Medicine, Furtwangen University, Villingen-Schwenningen, Baden-Württemberg, Germany.
Source: Bulletin of mathematical biology [Bull Math Biol] 2024 May 08; Vol. 86 (6), pp. 70. Date of Electronic Publication: 2024 May 08.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Springer Country of Publication: United States NLM ID: 0401404 Publication Model: Electronic Cited Medium: Internet ISSN: 1522-9602 (Electronic) Linking ISSN: 00928240 NLM ISO Abbreviation: Bull Math Biol Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:1522-9602
DOI:10.1007/s11538-024-01304-1