Bioimaging and the future of whole-organismal developmental physiology.
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| Format: | Artículo científico |
| Language: | en |
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Comparative biochemistry and physiology. Part A, Molecular & integrative physiology
2025
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| _version_ | 1868266277669175296 |
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| author | Tills, Oliver Ibbini, Ziad Spicer, John I |
| author_facet | Tills, Oliver Ibbini, Ziad Spicer, John I Tills, Oliver Ibbini, Ziad Spicer, John I |
| collection | PubMed - marine biology |
| contents | Bioimaging and the future of whole-organismal developmental physiology. Tills, Oliver Ibbini, Ziad Spicer, John I Animals Humans Deep Learning Developmental Biology Image Processing, Computer-Assisted While omics has transformed the study of biology, concomitant advances made at the level of the whole organism, i.e. the phenome, have arguably not kept pace with lower levels of biological organisation. In this personal commentary we evaluate the importance of imaging as a means of measuring whole organismal developmental physiology. Image acquisition, while an important process itself, has become secondary to image analysis as a bottleneck to the use of imaging in research. Here, we explore the significant potential for increasingly sophisticated approaches to image analysis, including deep learning, to advance our understanding of how developing animals grow and function. Furthermore, unlike many species-specific methodologies, tools and technologies, we explore how computer vision has the potential to be transferable between species, life stages, experiments and even taxa in which embryonic development can be imaged. We identify what we consider are six of the key challenges and opportunities in the application of computer vision to developmental physiology carried out in our lab, and more generally. We reflect on the tangibility of transferrable computer vision models capable of measuring the integrative physiology of a broad range of developing organisms, and thereby driving the adoption of phenomics for developmental physiology. We are at an exciting time of witnessing the move from computer vision as a replacement for manual observation, or manual image analysis, to it enabling a fundamentally more powerful approach to exploring and understanding the complex biology of developing organisms, the quantification of which has long posed a challenge to researchers. |
| format | Artículo científico |
| id | pubmed_39581226 |
| institution | PubMed |
| language | en |
| publishDate | 2025 |
| publisher | Comparative biochemistry and physiology. Part A, Molecular & integrative physiology |
| record_format | pubmed |
| spellingShingle | Bioimaging and the future of whole-organismal developmental physiology. Tills, Oliver Ibbini, Ziad Spicer, John I Animals Humans Deep Learning Developmental Biology Image Processing, Computer-Assisted Bioimaging and the future of whole-organismal developmental physiology. Tills, Oliver Ibbini, Ziad Spicer, John I Animals Humans Deep Learning Developmental Biology Image Processing, Computer-Assisted While omics has transformed the study of biology, concomitant advances made at the level of the whole organism, i.e. the phenome, have arguably not kept pace with lower levels of biological organisation. In this personal commentary we evaluate the importance of imaging as a means of measuring whole organismal developmental physiology. Image acquisition, while an important process itself, has become secondary to image analysis as a bottleneck to the use of imaging in research. Here, we explore the significant potential for increasingly sophisticated approaches to image analysis, including deep learning, to advance our understanding of how developing animals grow and function. Furthermore, unlike many species-specific methodologies, tools and technologies, we explore how computer vision has the potential to be transferable between species, life stages, experiments and even taxa in which embryonic development can be imaged. We identify what we consider are six of the key challenges and opportunities in the application of computer vision to developmental physiology carried out in our lab, and more generally. We reflect on the tangibility of transferrable computer vision models capable of measuring the integrative physiology of a broad range of developing organisms, and thereby driving the adoption of phenomics for developmental physiology. We are at an exciting time of witnessing the move from computer vision as a replacement for manual observation, or manual image analysis, to it enabling a fundamentally more powerful approach to exploring and understanding the complex biology of developing organisms, the quantification of which has long posed a challenge to researchers. |
| title | Bioimaging and the future of whole-organismal developmental physiology. |
| topic | Animals Humans Deep Learning Developmental Biology Image Processing, Computer-Assisted |
| url | https://pubmed.ncbi.nlm.nih.gov/39581226/ |