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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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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Oxford University Press
2023
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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 |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-10354001 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT leedaewon lpfaframeworkforexploringthewingcolorpatternformationofladybirdbeetlesinpython |