An AI Agent for Fully Automated Multi‐Omic Analyses
Abstract With the fast‐growing and evolving omics data, the demand for streamlined and adaptable tools to handle bioinformatics analysis continues to grow. In response to this need, Automated Bioinformatics Analysis (AutoBA) is introduced, an autonomous AI agent designed explicitly for fully automat...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-11-01
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| Series: | Advanced Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/advs.202407094 |
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| _version_ | 1846151505367793664 |
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| author | Juexiao Zhou Bin Zhang Guowei Li Xiuying Chen Haoyang Li Xiaopeng Xu Siyuan Chen Wenjia He Chencheng Xu Liwei Liu Xin Gao |
| author_facet | Juexiao Zhou Bin Zhang Guowei Li Xiuying Chen Haoyang Li Xiaopeng Xu Siyuan Chen Wenjia He Chencheng Xu Liwei Liu Xin Gao |
| author_sort | Juexiao Zhou |
| collection | DOAJ |
| description | Abstract With the fast‐growing and evolving omics data, the demand for streamlined and adaptable tools to handle bioinformatics analysis continues to grow. In response to this need, Automated Bioinformatics Analysis (AutoBA) is introduced, an autonomous AI agent designed explicitly for fully automated multi‐omic analyses based on large language models (LLMs). AutoBA simplifies the analytical process by requiring minimal user input while delivering detailed step‐by‐step plans for various bioinformatics tasks. AutoBA's unique capacity to self‐design analysis processes based on input data variations further underscores its versatility. Compared with online bioinformatic services, AutoBA offers multiple LLM backends, with options for both online and local usage, prioritizing data security and user privacy. In comparison to ChatGPT and open‐source LLMs, an automated code repair (ACR) mechanism in AutoBA is designed to improve its stability in automated end‐to‐end bioinformatics analysis tasks. Moreover, different from the predefined pipeline, AutoBA has adaptability in sync with emerging bioinformatics tools. Overall, AutoBA represents an advanced and convenient tool, offering robustness and adaptability for conventional multi‐omic analyses. |
| format | Article |
| id | doaj-art-ee72c6f9d6f34f2399c301e1acfd5f1f |
| institution | Kabale University |
| issn | 2198-3844 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advanced Science |
| spelling | doaj-art-ee72c6f9d6f34f2399c301e1acfd5f1f2024-11-27T11:21:53ZengWileyAdvanced Science2198-38442024-11-011144n/an/a10.1002/advs.202407094An AI Agent for Fully Automated Multi‐Omic AnalysesJuexiao Zhou0Bin Zhang1Guowei Li2Xiuying Chen3Haoyang Li4Xiaopeng Xu5Siyuan Chen6Wenjia He7Chencheng Xu8Liwei Liu9Xin Gao10Computer Science Program Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955‐6900 Kingdom of Saudi ArabiaComputer Science Program Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955‐6900 Kingdom of Saudi ArabiaLaboratory of Health Intelligence Huawei Technologies Co., Ltd Shenzhen 210000 ChinaComputer Science Program Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955‐6900 Kingdom of Saudi ArabiaComputer Science Program Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955‐6900 Kingdom of Saudi ArabiaComputer Science Program Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955‐6900 Kingdom of Saudi ArabiaComputer Science Program Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955‐6900 Kingdom of Saudi ArabiaComputer Science Program Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955‐6900 Kingdom of Saudi ArabiaComputer Science Program Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955‐6900 Kingdom of Saudi ArabiaAdvanced Computing and Storage Laboratory Central Research Institute 2012 Laboratories, Huawei Technologies Co., Ltd Nanjing Jiangsu 210000 ChinaComputer Science Program Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955‐6900 Kingdom of Saudi ArabiaAbstract With the fast‐growing and evolving omics data, the demand for streamlined and adaptable tools to handle bioinformatics analysis continues to grow. In response to this need, Automated Bioinformatics Analysis (AutoBA) is introduced, an autonomous AI agent designed explicitly for fully automated multi‐omic analyses based on large language models (LLMs). AutoBA simplifies the analytical process by requiring minimal user input while delivering detailed step‐by‐step plans for various bioinformatics tasks. AutoBA's unique capacity to self‐design analysis processes based on input data variations further underscores its versatility. Compared with online bioinformatic services, AutoBA offers multiple LLM backends, with options for both online and local usage, prioritizing data security and user privacy. In comparison to ChatGPT and open‐source LLMs, an automated code repair (ACR) mechanism in AutoBA is designed to improve its stability in automated end‐to‐end bioinformatics analysis tasks. Moreover, different from the predefined pipeline, AutoBA has adaptability in sync with emerging bioinformatics tools. Overall, AutoBA represents an advanced and convenient tool, offering robustness and adaptability for conventional multi‐omic analyses.https://doi.org/10.1002/advs.202407094agentbioinformaticslarge language modelomics analysis |
| spellingShingle | Juexiao Zhou Bin Zhang Guowei Li Xiuying Chen Haoyang Li Xiaopeng Xu Siyuan Chen Wenjia He Chencheng Xu Liwei Liu Xin Gao An AI Agent for Fully Automated Multi‐Omic Analyses Advanced Science agent bioinformatics large language model omics analysis |
| title | An AI Agent for Fully Automated Multi‐Omic Analyses |
| title_full | An AI Agent for Fully Automated Multi‐Omic Analyses |
| title_fullStr | An AI Agent for Fully Automated Multi‐Omic Analyses |
| title_full_unstemmed | An AI Agent for Fully Automated Multi‐Omic Analyses |
| title_short | An AI Agent for Fully Automated Multi‐Omic Analyses |
| title_sort | ai agent for fully automated multi omic analyses |
| topic | agent bioinformatics large language model omics analysis |
| url | https://doi.org/10.1002/advs.202407094 |
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