人工智能与基于质谱的多模态分子剖析方法,促进传染病的治疗发现。

IF 12 1区 医学 Q1 PHARMACOLOGY & PHARMACY
Jingjing Liu , Chaohui Bao , Jiaxin Zhang , Zeguang Han , Hai Fang , Haitao Lu
{"title":"人工智能与基于质谱的多模态分子剖析方法,促进传染病的治疗发现。","authors":"Jingjing Liu ,&nbsp;Chaohui Bao ,&nbsp;Jiaxin Zhang ,&nbsp;Zeguang Han ,&nbsp;Hai Fang ,&nbsp;Haitao Lu","doi":"10.1016/j.pharmthera.2024.108712","DOIUrl":null,"url":null,"abstract":"<div><p>Infectious diseases, driven by a diverse array of pathogens, can swiftly undermine public health systems. Accurate diagnosis and treatment of infectious diseases—centered around the identification of biomarkers and the elucidation of disease mechanisms—are in dire need of more versatile and practical analytical approaches. Mass spectrometry (MS)-based molecular profiling methods can deliver a wealth of information on a range of functional molecules, including nucleic acids, proteins, and metabolites. While MS-driven omics analyses can yield vast datasets, the sheer complexity and multi-dimensionality of MS data can significantly hinder the identification and characterization of functional molecules within specific biological processes and events. Artificial intelligence (AI) emerges as a potent complementary tool that can substantially enhance the processing and interpretation of MS data. AI applications in this context lead to the reduction of spurious signals, the improvement of precision, the creation of standardized analytical frameworks, and the increase of data integration efficiency. This critical review emphasizes the pivotal roles of MS based omics strategies in the discovery of biomarkers and the clarification of infectious diseases. Additionally, the review underscores the transformative ability of AI techniques to enhance the utility of MS-based molecular profiling in the field of infectious diseases by refining the quality and practicality of data produced from omics analyses. In conclusion, we advocate for a forward-looking strategy that integrates AI with MS-based molecular profiling. This integration aims to transform the analytical landscape and the performance of biological molecule characterization, potentially down to the single-cell level. Such advancements are anticipated to propel the development of AI-driven predictive models, thus improving the monitoring of diagnostics and therapeutic discovery for the ongoing challenge related to infectious diseases.</p></div>","PeriodicalId":402,"journal":{"name":"Pharmacology & Therapeutics","volume":"263 ","pages":"Article 108712"},"PeriodicalIF":12.0000,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence with mass spectrometry-based multimodal molecular profiling methods for advancing therapeutic discovery of infectious diseases\",\"authors\":\"Jingjing Liu ,&nbsp;Chaohui Bao ,&nbsp;Jiaxin Zhang ,&nbsp;Zeguang Han ,&nbsp;Hai Fang ,&nbsp;Haitao Lu\",\"doi\":\"10.1016/j.pharmthera.2024.108712\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Infectious diseases, driven by a diverse array of pathogens, can swiftly undermine public health systems. Accurate diagnosis and treatment of infectious diseases—centered around the identification of biomarkers and the elucidation of disease mechanisms—are in dire need of more versatile and practical analytical approaches. Mass spectrometry (MS)-based molecular profiling methods can deliver a wealth of information on a range of functional molecules, including nucleic acids, proteins, and metabolites. While MS-driven omics analyses can yield vast datasets, the sheer complexity and multi-dimensionality of MS data can significantly hinder the identification and characterization of functional molecules within specific biological processes and events. Artificial intelligence (AI) emerges as a potent complementary tool that can substantially enhance the processing and interpretation of MS data. AI applications in this context lead to the reduction of spurious signals, the improvement of precision, the creation of standardized analytical frameworks, and the increase of data integration efficiency. This critical review emphasizes the pivotal roles of MS based omics strategies in the discovery of biomarkers and the clarification of infectious diseases. Additionally, the review underscores the transformative ability of AI techniques to enhance the utility of MS-based molecular profiling in the field of infectious diseases by refining the quality and practicality of data produced from omics analyses. In conclusion, we advocate for a forward-looking strategy that integrates AI with MS-based molecular profiling. This integration aims to transform the analytical landscape and the performance of biological molecule characterization, potentially down to the single-cell level. Such advancements are anticipated to propel the development of AI-driven predictive models, thus improving the monitoring of diagnostics and therapeutic discovery for the ongoing challenge related to infectious diseases.</p></div>\",\"PeriodicalId\":402,\"journal\":{\"name\":\"Pharmacology & Therapeutics\",\"volume\":\"263 \",\"pages\":\"Article 108712\"},\"PeriodicalIF\":12.0000,\"publicationDate\":\"2024-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pharmacology & Therapeutics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0163725824001323\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmacology & Therapeutics","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0163725824001323","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0

摘要

由各种病原体引起的传染病会迅速破坏公共卫生系统。传染病的准确诊断和治疗以生物标志物的鉴定和疾病机理的阐明为中心,亟需更多用途和实用的分析方法。以质谱(MS)为基础的分子剖析方法可以提供包括核酸、蛋白质和代谢物在内的一系列功能分子的大量信息。虽然 MS 驱动的全息分析可以产生庞大的数据集,但 MS 数据的复杂性和多维性会严重阻碍对特定生物过程和事件中功能分子的识别和表征。人工智能(AI)作为一种有效的补充工具,可以大大提高 MS 数据的处理和解释能力。人工智能在这方面的应用可减少虚假信号、提高精确度、创建标准化分析框架并提高数据整合效率。这篇重要综述强调了基于 MS 的全局策略在发现生物标记物和阐明传染病方面的关键作用。此外,本综述还强调了人工智能技术的变革能力,即通过改进全局分析产生的数据的质量和实用性,提高基于 MS 的分子剖析在传染病领域的实用性。总之,我们主张采取前瞻性战略,将人工智能与基于 MS 的分子图谱分析相结合。这种整合的目的是改变生物分子表征的分析格局和性能,有可能达到单细胞水平。预计这种进步将推动人工智能驱动的预测模型的发展,从而改善诊断监测和治疗发现,应对与传染病有关的持续挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence with mass spectrometry-based multimodal molecular profiling methods for advancing therapeutic discovery of infectious diseases

Infectious diseases, driven by a diverse array of pathogens, can swiftly undermine public health systems. Accurate diagnosis and treatment of infectious diseases—centered around the identification of biomarkers and the elucidation of disease mechanisms—are in dire need of more versatile and practical analytical approaches. Mass spectrometry (MS)-based molecular profiling methods can deliver a wealth of information on a range of functional molecules, including nucleic acids, proteins, and metabolites. While MS-driven omics analyses can yield vast datasets, the sheer complexity and multi-dimensionality of MS data can significantly hinder the identification and characterization of functional molecules within specific biological processes and events. Artificial intelligence (AI) emerges as a potent complementary tool that can substantially enhance the processing and interpretation of MS data. AI applications in this context lead to the reduction of spurious signals, the improvement of precision, the creation of standardized analytical frameworks, and the increase of data integration efficiency. This critical review emphasizes the pivotal roles of MS based omics strategies in the discovery of biomarkers and the clarification of infectious diseases. Additionally, the review underscores the transformative ability of AI techniques to enhance the utility of MS-based molecular profiling in the field of infectious diseases by refining the quality and practicality of data produced from omics analyses. In conclusion, we advocate for a forward-looking strategy that integrates AI with MS-based molecular profiling. This integration aims to transform the analytical landscape and the performance of biological molecule characterization, potentially down to the single-cell level. Such advancements are anticipated to propel the development of AI-driven predictive models, thus improving the monitoring of diagnostics and therapeutic discovery for the ongoing challenge related to infectious diseases.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
23.00
自引率
0.70%
发文量
222
审稿时长
90 days
期刊介绍: Pharmacology & Therapeutics, in its 20th year, delivers lucid, critical, and authoritative reviews on current pharmacological topics.Articles, commissioned by the editor, follow specific author instructions.This journal maintains its scientific excellence and ranks among the top 10 most cited journals in pharmacology.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信