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Mathematical model and genomics construction of developmental biology patterns using digital image technology
Biological pattern formation ensures that tissues and organs develop in the correct place and orientation within the body. A great deal has been learned about cell and tissue staining techniques, and today’s microscopes can capture digital images. A light microscope is an essential tool in biology a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9399364/ https://www.ncbi.nlm.nih.gov/pubmed/36035113 http://dx.doi.org/10.3389/fgene.2022.956415 |
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author | Ni, Shiwei Chen, Fei Chen, Guolong Yang, Yufeng |
author_facet | Ni, Shiwei Chen, Fei Chen, Guolong Yang, Yufeng |
author_sort | Ni, Shiwei |
collection | PubMed |
description | Biological pattern formation ensures that tissues and organs develop in the correct place and orientation within the body. A great deal has been learned about cell and tissue staining techniques, and today’s microscopes can capture digital images. A light microscope is an essential tool in biology and medicine. Analyzing the generated images will involve the creation of unique analytical techniques. Digital images of the material before and after deformation can be compared to assess how much strain and displacement the material responds. Furthermore, this article proposes Development Biology Patterns using Digital Image Technology (DBP-DIT) to cell image data in 2D, 3D, and time sequences. Engineered materials with high stiffness may now be characterized via digital image correlation. The proposed method of analyzing the mechanical characteristics of skin under various situations, such as one direction of stress and temperatures in the hundreds of degrees Celsius, is achievable using digital image correlation. A DBP-DIT approach to biological tissue modeling is based on digital image correlation (DIC) measurements to forecast the displacement field under unknown loading scenarios without presupposing a particular constitutive model form or owning knowledge of the material microstructure. A data-driven approach to modeling biological materials can be more successful than classical constitutive modeling if adequate data coverage and advice from partial physics constraints are available. The proposed procedures include a wide range of biological objectives, experimental designs, and laboratory preferences. The experimental results show that the proposed DBP-DIT achieves a high accuracy ratio of 99,3%, a sensitivity ratio of 98.7%, a specificity ratio of 98.6%, a probability index of 97.8%, a balanced classification ratio of 97.5%, and a low error rate of 38.6%. |
format | Online Article Text |
id | pubmed-9399364 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93993642022-08-25 Mathematical model and genomics construction of developmental biology patterns using digital image technology Ni, Shiwei Chen, Fei Chen, Guolong Yang, Yufeng Front Genet Genetics Biological pattern formation ensures that tissues and organs develop in the correct place and orientation within the body. A great deal has been learned about cell and tissue staining techniques, and today’s microscopes can capture digital images. A light microscope is an essential tool in biology and medicine. Analyzing the generated images will involve the creation of unique analytical techniques. Digital images of the material before and after deformation can be compared to assess how much strain and displacement the material responds. Furthermore, this article proposes Development Biology Patterns using Digital Image Technology (DBP-DIT) to cell image data in 2D, 3D, and time sequences. Engineered materials with high stiffness may now be characterized via digital image correlation. The proposed method of analyzing the mechanical characteristics of skin under various situations, such as one direction of stress and temperatures in the hundreds of degrees Celsius, is achievable using digital image correlation. A DBP-DIT approach to biological tissue modeling is based on digital image correlation (DIC) measurements to forecast the displacement field under unknown loading scenarios without presupposing a particular constitutive model form or owning knowledge of the material microstructure. A data-driven approach to modeling biological materials can be more successful than classical constitutive modeling if adequate data coverage and advice from partial physics constraints are available. The proposed procedures include a wide range of biological objectives, experimental designs, and laboratory preferences. The experimental results show that the proposed DBP-DIT achieves a high accuracy ratio of 99,3%, a sensitivity ratio of 98.7%, a specificity ratio of 98.6%, a probability index of 97.8%, a balanced classification ratio of 97.5%, and a low error rate of 38.6%. Frontiers Media S.A. 2022-08-10 /pmc/articles/PMC9399364/ /pubmed/36035113 http://dx.doi.org/10.3389/fgene.2022.956415 Text en Copyright © 2022 Ni, Chen, Chen and Yang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Ni, Shiwei Chen, Fei Chen, Guolong Yang, Yufeng Mathematical model and genomics construction of developmental biology patterns using digital image technology |
title | Mathematical model and genomics construction of developmental biology patterns using digital image technology |
title_full | Mathematical model and genomics construction of developmental biology patterns using digital image technology |
title_fullStr | Mathematical model and genomics construction of developmental biology patterns using digital image technology |
title_full_unstemmed | Mathematical model and genomics construction of developmental biology patterns using digital image technology |
title_short | Mathematical model and genomics construction of developmental biology patterns using digital image technology |
title_sort | mathematical model and genomics construction of developmental biology patterns using digital image technology |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9399364/ https://www.ncbi.nlm.nih.gov/pubmed/36035113 http://dx.doi.org/10.3389/fgene.2022.956415 |
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