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LPF: a framework for exploring the wing color pattern formation of ladybird beetles in Python

SUMMARY: Biological pattern formation is one of the complex system phenomena in nature, requiring theoretical analysis based on mathematical modeling and computer simulations for in-depth understanding. We propose a Python framework named LPF to systematically explore the highly diverse wing color p...

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Autor principal: Lee, Daewon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10354001/
https://www.ncbi.nlm.nih.gov/pubmed/37421407
http://dx.doi.org/10.1093/bioinformatics/btad430
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author Lee, Daewon
author_facet Lee, Daewon
author_sort Lee, Daewon
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description SUMMARY: Biological pattern formation is one of the complex system phenomena in nature, requiring theoretical analysis based on mathematical modeling and computer simulations for in-depth understanding. We propose a Python framework named LPF to systematically explore the highly diverse wing color patterns of ladybirds using reaction-diffusion models. LPF supports GPU-accelerated array computing for numerical analysis of partial differential equation models, concise visualization of ladybird morphs, and evolutionary algorithms for searching mathematical models with deep learning models for computer vision. AVAILABILITY AND IMPLEMENTATION: LPF is available on GitHub at https://github.com/cxinsys/lpf.
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spelling pubmed-103540012023-07-20 LPF: a framework for exploring the wing color pattern formation of ladybird beetles in Python Lee, Daewon Bioinformatics Applications Note SUMMARY: Biological pattern formation is one of the complex system phenomena in nature, requiring theoretical analysis based on mathematical modeling and computer simulations for in-depth understanding. We propose a Python framework named LPF to systematically explore the highly diverse wing color patterns of ladybirds using reaction-diffusion models. LPF supports GPU-accelerated array computing for numerical analysis of partial differential equation models, concise visualization of ladybird morphs, and evolutionary algorithms for searching mathematical models with deep learning models for computer vision. AVAILABILITY AND IMPLEMENTATION: LPF is available on GitHub at https://github.com/cxinsys/lpf. Oxford University Press 2023-07-08 /pmc/articles/PMC10354001/ /pubmed/37421407 http://dx.doi.org/10.1093/bioinformatics/btad430 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Lee, Daewon
LPF: a framework for exploring the wing color pattern formation of ladybird beetles in Python
title LPF: a framework for exploring the wing color pattern formation of ladybird beetles in Python
title_full LPF: a framework for exploring the wing color pattern formation of ladybird beetles in Python
title_fullStr LPF: a framework for exploring the wing color pattern formation of ladybird beetles in Python
title_full_unstemmed LPF: a framework for exploring the wing color pattern formation of ladybird beetles in Python
title_short LPF: a framework for exploring the wing color pattern formation of ladybird beetles in Python
title_sort lpf: a framework for exploring the wing color pattern formation of ladybird beetles in python
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10354001/
https://www.ncbi.nlm.nih.gov/pubmed/37421407
http://dx.doi.org/10.1093/bioinformatics/btad430
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