Evidence map›Paper›PMID 28703778›Full record

ArticleMetabolites2017

Natural Product Discovery Using Planes of Principal Component Analysis in R (PoPCAR).

Shaurya Chanana, Chris S Thomas, Doug R Braun, Yanpeng Hou, Thomas P Wyche, Tim S Bugni

Abstract read
In one paragraph

Article in Metabolites, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Article
  10. Review
  11. Synergistic effect of co-culture rhizosphereFrontiers in microbiology · 2022
    Article
  12. Review
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Metabolites · 2020
    Article
  19. Article
  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

6 authors.

Shaurya ChananaPharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin, Madison, WI 53705, USA. schanana@wisc.edu.
Chris S ThomasPharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin, Madison, WI 53705, USA. csthomas4@wisc.edu.
Doug R BraunPharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin, Madison, WI 53705, USA. drbraun1@wisc.edu.
Yanpeng HouPharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin, Madison, WI 53705, USA. yanpenghou@gmail.com.
Thomas P WychePharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin, Madison, WI 53705, USA. thomas.wyche@merck.com.
Tim S BugniPharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin, Madison, WI 53705, USA. tim.bugni@wisc.edu.

Funding

Omics approaches for natural products discoveryR01GM104192 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI BUGNI, TIMOTHY S · 2013 to 2019
$2.0M
NIGMS NIH HHS R01 GM104192
6 · The paper itself

Abstract

Rediscovery of known natural products hinders the discovery of new, unique scaffolds. Efforts have mostly focused on streamlining the determination of what compounds are known vs. unknown (dereplication), but an alternative strategy is to focus on what is different. Utilizing statistics and assuming that common actinobacterial metabolites are likely known, focus can be shifted away from dereplication and towards discovery. LC-MS-based principal component analysis (PCA) provides a perfect tool to distinguish unique vs. common metabolites, but the variability inherent within natural products leads to datasets that do not fit ideal standards. To simplify the analysis of PCA models, we developed a script that identifies only those masses or molecules that are unique to each strain within a group, thereby greatly reducing the number of data points to be inspected manually. Since the script is written in R, it facilitates integration with other metabolomics workflows and supports automated mass matching to databases such as Antibase.

Indexed as

actinobacteriamarine actinomycetesmass spectrometrymetabolomicsprincipal component analysis

Identifiers

PMID28703778
PMCPMC5618319

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.