Evidence map›Paper›PMID 38007419›Full record

ArticleBMC genomics2023

Using published pathway figures in enrichment analysis and machine learning.

Min-Gyoung Shin, Alexander R Pico

Abstract read
In one paragraph

Article in BMC genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. lncRNAlyzr: Enrichment Analysis for lncRNA Sets.Journal of molecular biology · 2025
    Article
  5. Pathway Analysis Interpretation in the Multi-Omic Era.Biotech (Basel (Switzerland)) · 2025
    Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Min-Gyoung ShinInstitute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA.
Alexander R PicoInstitute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA. alex.pico@gladstone.ucsf.edu.

Funding

TR&D 3 - Network Guided Machine LearningP41GM103504 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IDEKER, TREY · 2012 to 2024
$17.3M
WikiPathways Project: At the Intersection of Big Data and Researcher KnowledgeR01GM100039 · NIGMS · J. DAVID GLADSTONE INSTITUTES · PI PICO, ALEXANDER R · 2012 to 2020
$3.4M
NIGMS NIH HHS P41 GM103504NIGMS NIH HHS P41GM103504NIGMS NIH HHS R01 GM100039NIGMS NIH HHS R01GM100039
6 · The paper itself

Abstract

Pathway Figure OCR (PFOCR) is a novel kind of pathway database approaching the breadth and depth of Gene Ontology while providing rich, mechanistic diagrams and direct literature support. Here, we highlight the utility of PFOCR in disease research in comparison with popular pathway databases through an assessment of disease coverage and analytical applications. In addition to common pathway analysis use cases, we present two advanced case studies demonstrating unique advantages of PFOCR in terms of cancer subtype and grade prediction analyses.

Indexed as

Machine LearningNeoplasmsDatabases, FactualGene OntologyHumansDatabase comparisonDisease mechanismEnrichment analysisMachine learningPathway database

Identifiers

PMID38007419
PMCPMC10676589

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.