Evidence map›Paper›PMID 37004072›Full record

ArticleJournal of cheminformatics2023

qHTSWaterfall: 3-dimensional visualization software for quantitative high-throughput screening (qHTS) data.

Bryan Queme, John C Braisted, Patricia Dranchak, James Inglese

Abstract read
In one paragraph

Article in Journal of cheminformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Machine Learning Models Identify Inhibitors of New Delhi Metallo-β-lactamase.Journal of chemical information and modeling · 2024
    Article
  4. 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

4 authors.

Bryan QuemeNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, 20850, USA.ORCID http://orcid.org/0000-0003-1509-9982
John C BraistedNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, 20850, USA. john.braisted@nih.gov.ORCID http://orcid.org/0000-0001-8093-6463
Patricia DranchakNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, 20850, USA.ORCID http://orcid.org/0000-0002-1349-4885
James IngleseNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, 20850, USA.ORCID http://orcid.org/0000-0002-7332-5717

Funding

Informatics Research CoreZICTR000410 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI MATHÉ, EWY · 2021 to 2025
$11.7M
Target-based Assays and Screening Strategies for Chemical Probe and Therapeutic Lead DiscoveryZIATR000053 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI INGLESE, JAMES · 2015 to 2025
$4.5M
Phenotypic Assay Design and Development for Rare and Neglected DiseasesZIATR000052 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI INGLESE, JAMES · 2015 to 2025
$3.7M
Intramural Research Program of the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH) 1ZIATR000052
6 · The paper itself

Abstract

High throughput screening (HTS) is widely used in drug discovery and chemical biology to identify and characterize agents having pharmacologic properties often by evaluation of large chemical libraries. Standard HTS data can be simply plotted as an x-y graph usually represented as % activity of a compound tested at a single concentration vs compound ID, whereas quantitative HTS (qHTS) data incorporates a third axis represented by concentration. By virtue of the additional data points arising from the compound titration and the incorporation of logistic fit parameters that define the concentration-response curve, such as EC50 and Hill slope, qHTS data has been challenging to display on a single graph. Here we provide a flexible solution to the rapid plotting of complete qHTS data sets to produce a 3-axis plot we call qHTS Waterfall Plots. The software described here can be generally applied to any 3-axis dataset and is available as both an R package and an R shiny application.

Indexed as

3-axis plotsConcentration–responseDose–responseEfficacyPharmacologyqHTS Waterfall plotsQuantitative high-throughput screening

Identifiers

PMID37004072
PMCPMC10064508

What Socratic 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 Socratic graph.