Evidence map›Paper›PMID 31736866›Full record

ArticleFrontiers in neurology2019

A Machine Learning Method for Identifying Critical Interactions Between Gene Pairs in Alzheimer's Disease Prediction.

Hao Chen, Yong He, Jiadong Ji, Yufeng Shi

Abstract read
In one paragraph

Article in Frontiers in neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Single-cell genomics and regulatory networks for 388 human brains.bioRxiv : the preprint server for biology · 2024
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. 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.

Hao ChenSchool of Statistics, Shandong University of Finance and Economics, Jinan, China.
Yong HeSchool of Statistics, Shandong University of Finance and Economics, Jinan, China.
Jiadong JiSchool of Statistics, Shandong University of Finance and Economics, Jinan, China.
Yufeng ShiInstitute for Financial Studies and School of Mathematics, Shandong University, Jinan, China.

Funding

Alzheimer's Disease Genetics ConsortiumU01AG032984 · NIA · UNIVERSITY OF PENNSYLVANIA · PI SCHELLENBERG, GERARD DAVID · 2009 to 2024
$60.4M
SUPPLEMENT TO RUSH ALZHEIMERS DISEASE CENTER COREP30AG010161 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI LEURGANS, SUE E. · 1991 to 2020
$49.1M
EPIDEMIOLOGY OF NEURAL RESERVE AND NEUROBIOLOGY IN AGINGR01AG017917 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 2001 to 2023
$43.3M
RISK FACTORS, PATHOLOGY, AND CLINICAL EXPRESSIONS OF ADR01AG015819 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1998 to 2024
$21.4M
Pathway discovery, validation and compound identification for Alzheimer's disease - SupplementU01AG046152 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BENNETT, DAVID ALAN, DE JAGER, PHILIP L · 2013 to 2017
$13.6M
Genetic Epidemiology of Cognitive Decline in an Aging Population SampleR01AG030146 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI EVANS, DENIS A · 2007 to 2018
$6.2M
Exploring the Role of the Brain Transcriptome in Cognitive DeclineR01AG036836 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI DE JAGER, PHILIP L · 2011 to 2014
$2.9M
NIA NIH HHS P30 AG010161NIA NIH HHS R01 AG015819NIA NIH HHS R01 AG017917NIA NIH HHS R01 AG030146NIA NIH HHS R01 AG036836NIA NIH HHS U01 AG032984NIA NIH HHS U01 AG046152
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Alzheimer's diseasedifferential networksgene expressionmachine learningneurodegenerative disease

Identifiers

PMID31736866
PMCPMC6834789

What OpenQuestion holds

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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.