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前沿人工智能工具正在彻底改变生命科学领域的科学研究。

Cutting-edge AI tools revolutionizing scientific research in life sciences.

作者信息

Lorenc-KuKu A Katarzyna

机构信息

Translmed Publishing Group, Wieluñ, Poland.

出版信息

BioTechnologia (Pozn). 2025 Mar 31;106(1):77-102. doi: 10.5114/bta/200803. eCollection 2025.

DOI:10.5114/bta/200803
PMID:40401131
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12089930/
Abstract

Artificial intelligence (AI) is becoming a transformative force in the life sciences, pushing the boundaries of possibility. Imagine AI automating time-consuming tasks, uncovering hidden patterns in vast datasets, designing proteins in minutes instead of years, and even predicting disease outbreaks before they occur. This review explores the latest AI tools revolutionizing scientific fields, including research and data analysis, healthcare, and tools supporting scientific writing. Beyond data processing, AI is reshaping how scientists draft and share their findings, enhancing processes ranging from literature reviews to citation management. However, with great power comes great responsibility. Are we prepared for this leap? This review delves into the forefront of AI in the life sciences, where innovation meets responsibility.

摘要

人工智能(AI)正在成为生命科学领域的一股变革力量,拓展着可能性的边界。想象一下,人工智能能够自动执行耗时的任务,在海量数据集中发现隐藏的模式,在几分钟而非数年的时间里设计蛋白质,甚至在疾病爆发之前就进行预测。这篇综述探讨了正在彻底改变科学领域的最新人工智能工具,包括研究与数据分析、医疗保健以及支持科学写作的工具。除了数据处理,人工智能正在重塑科学家起草和分享研究结果的方式,改善从文献综述到引文管理等一系列流程。然而,能力越大,责任越大。我们是否为这一飞跃做好准备了呢?这篇综述深入探讨了生命科学领域人工智能的前沿动态,在这里创新与责任并存。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eed0/12089930/7655652a5045/BTA-106-1-200803-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eed0/12089930/7655652a5045/BTA-106-1-200803-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eed0/12089930/7655652a5045/BTA-106-1-200803-g001.jpg

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本文引用的文献

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The ethics of using artificial intelligence in scientific research: new guidance needed for a new tool.科学研究中使用人工智能的伦理问题:新工具需要新指南。
AI Ethics. 2025 Apr;5(2):1499-1521. doi: 10.1007/s43681-024-00493-8. Epub 2024 May 27.
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Challenges and applications of artificial intelligence in infectious diseases and antimicrobial resistance.人工智能在传染病和抗菌药物耐药性方面的挑战与应用
NPJ Antimicrob Resist. 2025 Jan 7;3(1):2. doi: 10.1038/s44259-024-00068-x.
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AI hallucinations can't be stopped - but these techniques can limit their damage.
人工智能幻觉无法被阻止——但这些技术可以限制其危害。
Nature. 2025 Jan;637(8047):778-780. doi: 10.1038/d41586-025-00068-5.
4
AI-designed proteins tackle century-old problem - making snake antivenoms.人工智能设计的蛋白质攻克了一个百年难题——制造蛇毒抗毒素。
Nature. 2025 Jan;637(8047):776. doi: 10.1038/d41586-025-00133-z.
5
AlphaFold 3 is great - but it still needs human help to get chemistry right.阿尔法折叠3很强大——但要想让化学原理正确无误,它仍需要人工协助。
Nature. 2025 Jan;637(8046):548. doi: 10.1038/d41586-025-00111-5.
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Use of Artificial Intelligence in Peer Review Among Top 100 Medical Journals.人工智能在排名前100的医学期刊同行评审中的应用。
JAMA Netw Open. 2024 Dec 2;7(12):e2448609. doi: 10.1001/jamanetworkopen.2024.48609.
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Evaluation of large language models for discovery of gene set function.用于发现基因集功能的大语言模型评估
Nat Methods. 2025 Jan;22(1):82-91. doi: 10.1038/s41592-024-02525-x. Epub 2024 Nov 28.
8
CelloType: a unified model for segmentation and classification of tissue images.细胞类型:一种用于组织图像分割和分类的统一模型。
Nat Methods. 2025 Feb;22(2):348-357. doi: 10.1038/s41592-024-02513-1. Epub 2024 Nov 22.
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Nature. 2024 Nov;635(8040):808-811. doi: 10.1038/d41586-024-03815-2.
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A foundation model for joint segmentation, detection and recognition of biomedical objects across nine modalities.一种用于跨九种模态对生物医学对象进行联合分割、检测和识别的基础模型。
Nat Methods. 2025 Jan;22(1):166-176. doi: 10.1038/s41592-024-02499-w. Epub 2024 Nov 18.