Evidence map›Paper›PMID 32708222›Full record

ArticleMetabolites2020

Shaurya Chanana, Chris S Thomas, Fan Zhang, Scott R Rajski, Tim S Bugni

Abstract read
In one paragraph

Article in Metabolites, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Leaf Blight inPlants (Basel, Switzerland) · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Frontiers in plant science · 2025
    Article
  14. Article
  15. The Ectopic Expression of thePlants (Basel, Switzerland) · 2024
    Article
  16. Article
  17. Article
  18. Review
  19. Modern Trends in Natural Antibiotic Discovery.Life (Basel, Switzerland) · 2023
    Review
  20. Article
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

5 authors.

Shaurya ChananaPharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin, Madison, WI 53705, USA.ORCID 0000-0002-3021-2210
Chris S ThomasPharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin, Madison, WI 53705, USA.ORCID 0000-0002-4541-1634
Fan ZhangPharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin, Madison, WI 53705, USA.
Scott R RajskiPharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin, Madison, WI 53705, USA.ORCID 0000-0002-0238-8411
Tim S BugniPharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin, Madison, WI 53705, USA.ORCID 0000-0002-4502-3084

Funding

Novel antimicrobials targeting MDR pathogens from animal microbial symbiontsU19AI142720 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI ANDES, DAVID R · 2019 to 2023
$30.1M
Metabolomics driven discovery of drug leads from symbiotic bacteriaU19AI109673 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI ANDES, DAVID R, CURRIE, CAMERON ROBERT · 2014 to 2018
$16.2M
Novel therapeutic agents from the bacterial symbionts of Brazilian invertebratesU19TW009872 · FIC · HARVARD MEDICAL SCHOOL · PI CLARDY, JON, PUPO, MONICA T · 2014 to 2018
$4.4M
Omics approaches for natural products discoveryR01GM104192 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI BUGNI, TIMOTHY S · 2013 to 2019
$2.0M
FIC NIH HHS U19 TW009872NIAID NIH HHS U19 AI109673NIAID NIH HHS U19 AI142720NIGMS NIH HHS R01 GM104192NIH HHS R01 GM104192NIH HHS U19 TW009872
6 · The paper itself

Abstract

Microbial natural product discovery programs face two main challenges today: rapidly prioritizing strains for discovering new molecules and avoiding the rediscovery of already known molecules. Typically, these problems have been tackled using biological assays to identify promising strains and techniques that model variance in a dataset such as PCA to highlight novel chemistry. While these tools have shown successful outcomes in the past, datasets are becoming much larger and require a new approach. Since PCA models are dependent on the members of the group being modeled, large datasets with many members make it difficult to accurately model the variance in the data. Our tool,

Indexed as

dendrogramgenomicsHCALCMSmetabolitesopen sourcePCAvariance

Identifiers

PMID32708222
PMCPMC7407629

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.