Fast and accurate identification of pathogenic bacteria using excitation–emission spectroscopy and machine learning-Reference-Cited by-同舟云学术

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Fast and accurate identification of pathogenic bacteria using excitation–emission spectroscopy and machine learning

Published:2024 Issue:8 Volume:3 Page:1253-1262
ISSN:2635-0998
Container-title:Sensors & Diagnostics
language:en
Short-container-title:Sens. Diagn.

Author:

Henry Jacob¹,Endres Jennifer L.²,Sadykov Marat R.²,Bayles Kenneth W.²,Svechkarev Denis¹^ORCID

Affiliation:

1. Department of Chemistry, University of Nebraska at Omaha, 6601 University Drive North, Omaha, NE 68182-0109, USA

2. Department of Pathology, Microbiology, and Immunology, University of Nebraska Medical Center, Omaha NE, USA

Abstract

Integration of multidimensional fluorescence spectroscopy of an environmentally sensitive dye and pattern recognition offers a quick and accurate approach to identification of pathogenic bacteria.

Funder

University of Nebraska Omaha

National Institute of Allergy and Infectious Diseases

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/SD/D4SD00070F

Reference38 articles.

1. Advances in Chemical and Biological Methods to Identify Microorganisms—From Past to Present

2. Emerging Technologies for Molecular Diagnosis of Sepsis

3. Developing a toll-like receptor biosensor for Gram-positive bacterial detection and its storage strategies

4. Sandwich antibody-based biosensor system for identification of Mycobacterium tuberculosis complex and nontuberculous mycobacteria

5. Detecting and Discriminating Shigella sonnei Using an Aptamer-Based Fluorescent Biosensor Platform

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