SemiSynBio: A new era for neuromorphic computing

IF 4.4 2区 生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Synthetic and Systems Biotechnology Pub Date : 2024-04-18 DOI:10.1016/j.synbio.2024.04.013
Ruicun Liu , Tuoyu Liu , Wuge Liu , Boyu Luo , Yuchen Li , Xinyue Fan , Xianchao Zhang , Wei Cui , Yue Teng
{"title":"SemiSynBio: A new era for neuromorphic computing","authors":"Ruicun Liu ,&nbsp;Tuoyu Liu ,&nbsp;Wuge Liu ,&nbsp;Boyu Luo ,&nbsp;Yuchen Li ,&nbsp;Xinyue Fan ,&nbsp;Xianchao Zhang ,&nbsp;Wei Cui ,&nbsp;Yue Teng","doi":"10.1016/j.synbio.2024.04.013","DOIUrl":null,"url":null,"abstract":"<div><p>Neuromorphic computing has the potential to achieve the requirements of the next-generation artificial intelligence (AI) systems, due to its advantages of adaptive learning and parallel computing. Meanwhile, biocomputing has seen ongoing development with the rise of synthetic biology, becoming the driving force for new generation semiconductor synthetic biology (SemiSynBio) technologies. DNA-based biomolecules could potentially perform the functions of Boolean operators as logic gates and be used to construct artificial neural networks (ANNs), providing the possibility of executing neuromorphic computing at the molecular level. Herein, we briefly outline the principles of neuromorphic computing, describe the advances in DNA computing with a focus on synthetic neuromorphic computing, and summarize the major challenges and prospects for synthetic neuromorphic computing. We believe that constructing such synthetic neuromorphic circuits will be an important step toward realizing neuromorphic computing, which would be of widespread use in biocomputing, DNA storage, information security, and national defense.</p></div>","PeriodicalId":22148,"journal":{"name":"Synthetic and Systems Biotechnology","volume":"9 3","pages":"Pages 594-599"},"PeriodicalIF":4.4000,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405805X24000644/pdfft?md5=1e4605b2d76880602fd20da7183a1007&pid=1-s2.0-S2405805X24000644-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Synthetic and Systems Biotechnology","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405805X24000644","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Neuromorphic computing has the potential to achieve the requirements of the next-generation artificial intelligence (AI) systems, due to its advantages of adaptive learning and parallel computing. Meanwhile, biocomputing has seen ongoing development with the rise of synthetic biology, becoming the driving force for new generation semiconductor synthetic biology (SemiSynBio) technologies. DNA-based biomolecules could potentially perform the functions of Boolean operators as logic gates and be used to construct artificial neural networks (ANNs), providing the possibility of executing neuromorphic computing at the molecular level. Herein, we briefly outline the principles of neuromorphic computing, describe the advances in DNA computing with a focus on synthetic neuromorphic computing, and summarize the major challenges and prospects for synthetic neuromorphic computing. We believe that constructing such synthetic neuromorphic circuits will be an important step toward realizing neuromorphic computing, which would be of widespread use in biocomputing, DNA storage, information security, and national defense.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
SemiSynBio:神经形态计算的新时代
神经形态计算具有自适应学习和并行计算的优势,有望实现下一代人工智能(AI)系统的要求。同时,随着合成生物学的兴起,生物计算也在不断发展,成为新一代半导体合成生物学(SemiSynBio)技术的推动力。基于DNA的生物大分子有可能像逻辑门一样执行布尔运算符的功能,并用于构建人工神经网络(ANN),为在分子水平执行神经形态计算提供了可能。在此,我们简要概述了神经形态计算的原理,介绍了DNA计算的进展,重点关注合成神经形态计算,并总结了合成神经形态计算面临的主要挑战和前景。我们相信,构建这种合成神经形态电路将是实现神经形态计算的重要一步,它将在生物计算、DNA 存储、信息安全和国防领域得到广泛应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Synthetic and Systems Biotechnology
Synthetic and Systems Biotechnology BIOTECHNOLOGY & APPLIED MICROBIOLOGY-
CiteScore
6.90
自引率
12.50%
发文量
90
审稿时长
67 days
期刊介绍: Synthetic and Systems Biotechnology aims to promote the communication of original research in synthetic and systems biology, with strong emphasis on applications towards biotechnology. This journal is a quarterly peer-reviewed journal led by Editor-in-Chief Lixin Zhang. The journal publishes high-quality research; focusing on integrative approaches to enable the understanding and design of biological systems, and research to develop the application of systems and synthetic biology to natural systems. This journal will publish Articles, Short notes, Methods, Mini Reviews, Commentary and Conference reviews.
期刊最新文献
Semi-rational design and modification of phosphoketolase to improve the yield of tyrosol in Saccharomyces cerevisiae Pathway and protein channel engineering of Bacillus subtilis for improved production of desthiobiotin and biotin Harnessing microbial heterogeneity for improved biosynthesis fueled by synthetic biology Recent advances in the biosynthesis and production optimization of gentamicin: A critical review Coordinated regulation of two LacI family regulators, GvmR and GvmR2, on guvermectin production in Streptomyces caniferus
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1