Literature DB >> 36035113

Mathematical model and genomics construction of developmental biology patterns using digital image technology.

Shiwei Ni1, Fei Chen1, Guolong Chen2, Yufeng Yang1.   

Abstract

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%.
Copyright © 2022 Ni, Chen, Chen and Yang.

Entities:  

Keywords:  biology patterns; data-driven; digital image correlation; medicine; microscopes

Year:  2022        PMID: 36035113      PMCID: PMC9399364          DOI: 10.3389/fgene.2022.956415

Source DB:  PubMed          Journal:  Front Genet        ISSN: 1664-8021            Impact factor:   4.772


  18 in total

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Review 3.  Rethinking organoid technology through bioengineering.

Authors:  Elena Garreta; Roger D Kamm; Susana M Chuva de Sousa Lopes; Madeline A Lancaster; Ron Weiss; Xavier Trepat; Insoo Hyun; Nuria Montserrat
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4.  Digital image colorimetry detection of carbaryl in food samples based on liquid phase microextraction coupled with a microfluidic thread-based analytical device.

Authors:  Xu Jing; Huihui Wang; Xin Huang; Zhenjia Chen; Junling Zhu; Xiaowen Wang
Journal:  Food Chem       Date:  2020-09-03       Impact factor: 7.514

5.  Three-dimensional bio-printing of primary human hepatocellular carcinoma for personalized medicine.

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Journal:  Biomaterials       Date:  2020-09-22       Impact factor: 12.479

Review 6.  A comprehensive survey of regulatory network inference methods using single cell RNA sequencing data.

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Journal:  Brief Bioinform       Date:  2021-05-20       Impact factor: 11.622

7.  A cellular platform for the development of synthetic living machines.

Authors:  Douglas Blackiston; Emma Lederer; Sam Kriegman; Simon Garnier; Joshua Bongard; Michael Levin
Journal:  Sci Robot       Date:  2021-03-31

8.  Constructing Dynamic Functional Networks via Weighted Regularization and Tensor Low-Rank Approximation for Early Mild Cognitive Impairment Classification.

Authors:  Zhuqing Jiao; Yixin Ji; Jiahao Zhang; Haifeng Shi; Chuang Wang
Journal:  Front Cell Dev Biol       Date:  2021-01-11

9.  A New Algorithm for Digital Image Encryption Based on Chaos Theory.

Authors:  Yaghoub Pourasad; Ramin Ranjbarzadeh; Abbas Mardani
Journal:  Entropy (Basel)       Date:  2021-03-13       Impact factor: 2.524

Review 10.  In Situ Monitoring of Additive Manufacturing Using Digital Image Correlation: A Review.

Authors:  Filipa G Cunha; Telmo G Santos; José Xavier
Journal:  Materials (Basel)       Date:  2021-03-19       Impact factor: 3.623

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