Lucas Abello Castillo*, and , Martín Gutiérrez Pescarmona*,
{"title":"CELLM:连接自然语言处理和人工智能合成遗传电路设计。","authors":"Lucas Abello Castillo*, and , Martín Gutiérrez Pescarmona*, ","doi":"10.1021/acssynbio.5c00391","DOIUrl":null,"url":null,"abstract":"<p >The complexity of the genetic circuit design limits accessibility and efficiency in synthetic biology. This study presents an integrated system that combines Cello software with large language models (DeepSeek-R1, Phi-4) and the LangChain framework in Python, which allows the creation, analysis, and optimization of genetic circuits using natural language instructions. <i>CELLM</i> automates the translation of textual descriptions into functional designs using Cello v2.1 as the basis for circuit synthesis and LLM for the interpretation of biological requirements and logical optimization. To the best of our knowledge, this work sets a precedent as the first system that integrates language models with synthetic biology design tools such as Cello, demonstrating that natural language processing can be translated into functional biological designs. This approach removes barriers by allowing researchers without bioengineering expertise to prototype genetic circuits using simple instructions.</p>","PeriodicalId":26,"journal":{"name":"ACS Synthetic Biology","volume":"14 9","pages":"3799–3803"},"PeriodicalIF":3.9000,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CELLM: Bridging Natural Language Processing and Synthetic Genetic Circuit Design with AI\",\"authors\":\"Lucas Abello Castillo*, and , Martín Gutiérrez Pescarmona*, \",\"doi\":\"10.1021/acssynbio.5c00391\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >The complexity of the genetic circuit design limits accessibility and efficiency in synthetic biology. This study presents an integrated system that combines Cello software with large language models (DeepSeek-R1, Phi-4) and the LangChain framework in Python, which allows the creation, analysis, and optimization of genetic circuits using natural language instructions. <i>CELLM</i> automates the translation of textual descriptions into functional designs using Cello v2.1 as the basis for circuit synthesis and LLM for the interpretation of biological requirements and logical optimization. To the best of our knowledge, this work sets a precedent as the first system that integrates language models with synthetic biology design tools such as Cello, demonstrating that natural language processing can be translated into functional biological designs. This approach removes barriers by allowing researchers without bioengineering expertise to prototype genetic circuits using simple instructions.</p>\",\"PeriodicalId\":26,\"journal\":{\"name\":\"ACS Synthetic Biology\",\"volume\":\"14 9\",\"pages\":\"3799–3803\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Synthetic Biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acssynbio.5c00391\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Synthetic Biology","FirstCategoryId":"99","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acssynbio.5c00391","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
CELLM: Bridging Natural Language Processing and Synthetic Genetic Circuit Design with AI
The complexity of the genetic circuit design limits accessibility and efficiency in synthetic biology. This study presents an integrated system that combines Cello software with large language models (DeepSeek-R1, Phi-4) and the LangChain framework in Python, which allows the creation, analysis, and optimization of genetic circuits using natural language instructions. CELLM automates the translation of textual descriptions into functional designs using Cello v2.1 as the basis for circuit synthesis and LLM for the interpretation of biological requirements and logical optimization. To the best of our knowledge, this work sets a precedent as the first system that integrates language models with synthetic biology design tools such as Cello, demonstrating that natural language processing can be translated into functional biological designs. This approach removes barriers by allowing researchers without bioengineering expertise to prototype genetic circuits using simple instructions.
期刊介绍:
The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism.
Topics may include, but are not limited to:
Design and optimization of genetic systems
Genetic circuit design and their principles for their organization into programs
Computational methods to aid the design of genetic systems
Experimental methods to quantify genetic parts, circuits, and metabolic fluxes
Genetic parts libraries: their creation, analysis, and ontological representation
Protein engineering including computational design
Metabolic engineering and cellular manufacturing, including biomass conversion
Natural product access, engineering, and production
Creative and innovative applications of cellular programming
Medical applications, tissue engineering, and the programming of therapeutic cells
Minimal cell design and construction
Genomics and genome replacement strategies
Viral engineering
Automated and robotic assembly platforms for synthetic biology
DNA synthesis methodologies
Metagenomics and synthetic metagenomic analysis
Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction
Gene optimization
Methods for genome-scale measurements of transcription and metabolomics
Systems biology and methods to integrate multiple data sources
in vitro and cell-free synthetic biology and molecular programming
Nucleic acid engineering.