Biological Engineering: What does it mean? Where does it (need to) go?
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866915799112876032 |
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| author | Nuber, Ulrike A. Stein, Viktor |
| author_facet | Nuber, Ulrike A. Stein, Viktor |
| contents | Biological engineering, the convergence between engineering and biology, is at the forefront of significant advances in healthcare, agriculture, and environmental sustainability, making it highly relevant to current scientific and societal challenges. We take a comprehensive look at this broad and interdisciplinary domain, structure it into three main areas - bioinspired, biological and biohybrid approaches - and dissect inherent and fundamental challenges along with opportunities, highlighting specific examples. We describe how data-driven discovery and design, in conjunction with artificial intelligence, can mitigate the absence of reductionist models in these areas. Additionally, we address the education of a new generation of biological engineers, emphasizing mathematical, technical, and artificial intelligence frameworks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_26525 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Biological Engineering: What does it mean? Where does it (need to) go? Nuber, Ulrike A. Stein, Viktor Other Quantitative Biology Biological engineering, the convergence between engineering and biology, is at the forefront of significant advances in healthcare, agriculture, and environmental sustainability, making it highly relevant to current scientific and societal challenges. We take a comprehensive look at this broad and interdisciplinary domain, structure it into three main areas - bioinspired, biological and biohybrid approaches - and dissect inherent and fundamental challenges along with opportunities, highlighting specific examples. We describe how data-driven discovery and design, in conjunction with artificial intelligence, can mitigate the absence of reductionist models in these areas. Additionally, we address the education of a new generation of biological engineers, emphasizing mathematical, technical, and artificial intelligence frameworks. |
| title | Biological Engineering: What does it mean? Where does it (need to) go? |
| topic | Other Quantitative Biology |
| url | https://arxiv.org/abs/2510.26525 |