Evidence map›Paper›PMID 32040319›Full record

ArticleJournal of chemical information and modeling2020

The Metabolic Rainbow: Deep Learning Phase I Metabolism in Five Colors.

Na Le Dang, Matthew K Matlock, Tyler B Hughes, S Joshua Swamidass

Open access · greenAbstract read
In one paragraph

Article in Journal of chemical information and modeling, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
3.2field-weighted citation impact, top 7% of its field
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

32 citing papers in PubMed, 62 citations in OpenAlex.

  1. Article
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  6. Automated Annotation of Sites of Metabolism from Biotransformation Data.Journal of chemical information and modeling · 2025
    Article
  7. Article
  8. Article
  9. Bioactive structures for inhibitors ofFuture medicinal chemistry · 2025
    Article
  10. Article
  11. ComprehensiveFrontiers in veterinary science · 2025
    Article
  12. Phenoconversion andHepatology forum · 2025
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  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

4 authors at 1 institution in 1 country.

Na Le DangDepartment of Pathology and Immunology, Washington University School of Medicine, Campus Box 8118, 660 S. Euclid Ave., St. Louis, Missouri 63110, United States.ORCID 0000-0001-7458-1264
Matthew K MatlockDepartment of Pathology and Immunology, Washington University School of Medicine, Campus Box 8118, 660 S. Euclid Ave., St. Louis, Missouri 63110, United States.ORCID 0000-0003-3087-4027
Tyler B HughesDepartment of Pathology and Immunology, Washington University School of Medicine, Campus Box 8118, 660 S. Euclid Ave., St. Louis, Missouri 63110, United States.ORCID 0000-0001-6221-9014
S Joshua SwamidassDepartment of Pathology and Immunology, Washington University School of Medicine, Campus Box 8118, 660 S. Euclid Ave., St. Louis, Missouri 63110, United States.ORCID 0000-0003-2191-0778
Washington University in St. Louis · US

Funding

HIGH PERFORMANCE BIOMEDICAL IMAGING COMPUTER RESOURCESS10RR022984 · NCRR · WASHINGTON UNIVERSITY · PI PRIOR, FRED WILLIAM · 2009 to 2009
$1.9M
DATA AND TOOLS FOR MODELING METABOLISM AND REACTIVITYR01LM012222 · NLM · WASHINGTON UNIVERSITY · PI MILLER, GROVER P, SWAMIDASS, SANJAY JOSHUA · 2016 to 2019
$1.5M
Computationally modeling the impact of ontogeny on drug metabolic fateR01LM012482 · NLM · UNIV OF ARKANSAS FOR MED SCIS · PI MILLER, GROVER P, SWAMIDASS, SANJAY JOSHUA · 2016 to 2019
$1.3M
GPU COMPUTING RESOURCE TO ENABLE INNOVATION IN IMAGING AND NETWORK BIOLOGYS10OD018091 · OD · WASHINGTON UNIVERSITY · PI PAPPU, ROHIT V, PRIOR, FRED WILLIAM · 2014 to 2014
$598k
NCRR NIH HHS S10 RR022984NIH HHS S10 OD018091NLM NIH HHS R01 LM012222NLM NIH HHS R01 LM012482
6 · The paper itself

Abstract

Metabolism of drugs affects their absorption, distribution, efficacy, excretion, and toxicity profiles. Metabolism is routinely assessed experimentally using recombinant enzymes, human liver microsome, and animal models. Unfortunately, these experiments are expensive, time-consuming, and often extrapolate poorly to humans because they fail to capture the full breadth of metabolic reactions observed

Indexed as

Deep LearningAnimalsColorHumansMetabolic Networks and PathwaysMicrosomes, LiverNeural Networks, Computer

Identifiers

PMID32040319
PMCPMC8716320
OpenAlexW3006192253

What OpenQuestion holds

Textmetadata
LicenceTDM
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.