Evidence map›Paper›PMID 28165067›Full record

ArticleScientific reports2017

Microbial Typing by Machine Learned DNA Melt Signatures.

Nadya Andini, Bo Wang, Pornpat Athamanolap, Justin Hardick, Billie J Masek, Simone Thair, Anne Hu, Gideon Avornu, Stephen Peterson, Steven Cogill and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Article
  6. Design of a 2D Melting Curve-Based Multiplex PCR Assay for Detection of SARS-CoV-2/RSV/Influenza A-B.The Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Emerging Analytical Techniques for Rapid Pathogen Identification and Susceptibility Testing.Annual review of analytical chemistry (Palo Alto, Calif.) · 2019
    Review
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Nadya AndiniEmergency Medicine, Stanford University, Stanford, California, 94305, USA.
Bo WangComputer Science, Stanford University, Stanford, California, 94305, USA.
Pornpat AthamanolapBiomedical Engineering, The Johns Hopkins University, Baltimore, Maryland, 21218, USA.
Justin HardickInfectious Disease, Medicine, The Johns Hopkins University, Baltimore, Maryland, 21218, USA.
Billie J MasekEmergency Medicine, The Johns Hopkins University, Baltimore, Maryland, 21218, USA.
Simone ThairEmergency Medicine, Stanford University, Stanford, California, 94305, USA.
Anne HuEmergency Medicine, Stanford University, Stanford, California, 94305, USA.
Gideon AvornuEmergency Medicine, The Johns Hopkins University, Baltimore, Maryland, 21218, USA.
Stephen PetersonEmergency Medicine, The Johns Hopkins University, Baltimore, Maryland, 21218, USA.
Steven CogillEmergency Medicine, Stanford University, Stanford, California, 94305, USA.
Richard E RothmanInfectious Disease, Medicine, The Johns Hopkins University, Baltimore, Maryland, 21218, USA.
Karen C CarrollMedical Microbiology, Pathology, The Johns Hopkins University, Baltimore, Maryland, 21218, USA.
Charlotte A GaydosInfectious Disease, Medicine, The Johns Hopkins University, Baltimore, Maryland, 21218, USA.
Jeff Tza-Huei WangBiomedical Engineering, The Johns Hopkins University, Baltimore, Maryland, 21218, USA.
Serafim BatzoglouComputer Science, Stanford University, Stanford, California, 94305, USA.
Samuel YangEmergency Medicine, Stanford University, Stanford, California, 94305, USA.

Funding

A Droplet-based single cell platform for pathogen identification and ASTR01AI117032 · NIAID · JOHNS HOPKINS UNIVERSITY · PI LIAO, JOSEPH C, WANG, TZA-HUEI JEFF · 2015 to 2019
$5.7M
NIAID NIH HHS R01 AI117032
6 · The paper itself

Abstract

There is still an ongoing demand for a simple broad-spectrum molecular diagnostic assay for pathogenic bacteria. For this purpose, we developed a single-plex High Resolution Melt (HRM) assay that generates complex melt curves for bacterial identification. Using internal transcribed spacer (ITS) region as the phylogenetic marker for HRM, we observed complex melt curve signatures as compared to 16S rDNA amplicons with enhanced interspecies discrimination. We also developed a novel Naïve Bayes curve classification algorithm with statistical interpretation and achieved 95% accuracy in differentiating 89 bacterial species in our library using leave-one-out cross-validation. Pilot clinical validation of our method correctly identified the etiologic organisms at the species-level in 59 culture-positive mono-bacterial blood culture samples with 90% accuracy. Our findings suggest that broad bacterial sequences may be simply, reliably and automatically profiled by ITS HRM assay for clinical adoption.

Indexed as

Transition TemperatureBacteriaBacterial Typing TechniquesBayes TheoremDNA, BacterialDNA, Ribosomal SpacerMachine LearningPhylogenyDNA, BacterialDNA, Ribosomal Spacer

Identifiers

PMID28165067
PMCPMC5292719

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.