Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Methods of Classification and Identification01:28

Methods of Classification and Identification

Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...
Applications of Molecular Taxonomy01:20

Applications of Molecular Taxonomy

Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
MALDI-TOF Mass Spectrometry01:19

MALDI-TOF Mass Spectrometry

4.7K
Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.
Matrix-assisted laser desorption ionization (MALDI) is a commonly...
4.7K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Unveiling the protective mechanism of rapid microwave heating on Lactoferrin: insights from structural integrity and bioactivity.

Food research international (Ottawa, Ont.)·2026
Same author

An F-box protein OsFKF1 interacts with either OsGI or Hd1 and mediates the degradation of OsGI to control flowering time in rice.

Science advances·2026
Same author

A triple-network hydrogel synergistically constructed via hydrophobic interactions, hemicellulose-mediated Diels-Alder bonds, and Fe<sup>3+</sup> coordination for flexible sensors and TENGs.

Carbohydrate polymers·2026
Same author

Biofunctional Pectin Derived from Pomelo Peel: Structural Insights and Neuro-Gut Protective Mechanisms in Zebrafish under Bisphenol AF-Induced Neurotoxicity.

Research (Washington, D.C.)·2026
Same author

Untargeted GC-IMS Metabolomics of Wound Headspace for Bacterial Infection Biomarker Discovery.

Metabolites·2026
Same author

CerS2 Is a Druggable Target in Triple-Negative Breast Cancer.

Molecular cancer therapeutics·2026

相关实验视频

Updated: Jun 8, 2025

Capturing Actively Produced Microbial Volatile Organic Compounds from Human-Associated Samples with Vacuum-Assisted Sorbent Extraction
09:19

Capturing Actively Produced Microbial Volatile Organic Compounds from Human-Associated Samples with Vacuum-Assisted Sorbent Extraction

Published on: June 1, 2022

4.0K

通过挥发性有机化合物分析和深度学习,快速识别细菌.

Bowen Yan1, Lin Zeng1, Yanyi Lu1

  • 1Research Department, Daping Hosipital, Army Medical University, Chongqing, 400042, China.

BMC bioinformatics
|November 7, 2024
PubMed
概括

这项研究引入了一种使用挥发性有机化合物和深度学习快速识别细菌的新方法. 这种方法可以准确识别细菌物种,有助于精确的药物治疗和打击抗菌素耐药性.

关键词:
亚历克斯的网络亚历克斯的网络细菌的分类细菌的分类深度学习是一种深度学习.在GC-IMSS中.挥发性有机化合物分析分析

更多相关视频

Characterizing Bacterial Volatiles using Secondary Electrospray Ionization Mass Spectrometry SESI-MS
08:54

Characterizing Bacterial Volatiles using Secondary Electrospray Ionization Mass Spectrometry SESI-MS

Published on: June 8, 2011

18.0K
Identification of Rare Bacterial Pathogens by 16S rRNA Gene Sequencing and MALDI-TOF MS
06:34

Identification of Rare Bacterial Pathogens by 16S rRNA Gene Sequencing and MALDI-TOF MS

Published on: July 11, 2016

17.8K

相关实验视频

Last Updated: Jun 8, 2025

Capturing Actively Produced Microbial Volatile Organic Compounds from Human-Associated Samples with Vacuum-Assisted Sorbent Extraction
09:19

Capturing Actively Produced Microbial Volatile Organic Compounds from Human-Associated Samples with Vacuum-Assisted Sorbent Extraction

Published on: June 1, 2022

4.0K
Characterizing Bacterial Volatiles using Secondary Electrospray Ionization Mass Spectrometry SESI-MS
08:54

Characterizing Bacterial Volatiles using Secondary Electrospray Ionization Mass Spectrometry SESI-MS

Published on: June 8, 2011

18.0K
Identification of Rare Bacterial Pathogens by 16S rRNA Gene Sequencing and MALDI-TOF MS
06:34

Identification of Rare Bacterial Pathogens by 16S rRNA Gene Sequencing and MALDI-TOF MS

Published on: July 11, 2016

17.8K

科学领域:

  • 微生物学 微生物学
  • 计算生物学 计算生物学
  • 分析化学 分析化学

背景情况:

  • 由于滥用抗生素,抗菌素耐药性是一个日益增长的全球健康威胁.
  • 准确和快速的细菌鉴定对于有效的临床治疗和抗菌药物管理至关重要.
  • 目前用于细菌识别的方法可能耗时,延迟了适当的患者护理.

研究的目的:

  • 开发和评估一种用于细菌物种识别的自动化方法.
  • 利用挥发性有机化合物 (VOC) 和深度学习进行快速微生物分析.
  • 提高临床环境中细菌识别的速度和准确性.

主要方法:

  • 细菌培养产生的挥发性有机化合物 (VOC) 的分析.
  • 深度学习算法的应用,特别是数据增强的AlexNet,用于分类.
  • 使用交叉验证技术来评估分类准确性.

主要成果:

  • 亚历克斯网络模型在识别单个细菌培养物方面取得了很高的准确性 (99.24%).
  • 报道了混合细菌培养的准确鉴定率:金黄色葡萄球菌 (SA) 在98.6%,大肠杆菌 (EC) 在98.58%, Pseudomonas aeruginosa (PA) 在98.99%.
  • 数据增强显著提高了AlexNet模型的性能.

结论:

  • 这项研究提出了一种新的,快速的方法,用于自动化细菌识别.
  • 开发的方法利用VOC和深度学习,可以帮助临床医生快速识别细菌物种.
  • 准确及时识别有助于适当的抗生素处方,有助于疫情控制和减轻抗菌素耐药性的影响.