Evidence map›Paper›PMID 29487692›Full record

ArticleOncotarget2018

Use of deep neural network ensembles to identify embryonic-fetal transition markers: repression of

Michael D West, Ivan Labat, Hal Sternberg, Dana Larocca, Igor Nasonkin, Karen B Chapman, Ratnesh Singh, Eugene Makarev, Alex Aliper, Andrey Kazennov and 13 more

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Oncotarget, 2018. 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
1.4field-weighted citation impact, top 20% 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

23 citing papers in PubMed, 47 citations in OpenAlex.

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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

23 authors at 5 institutions in 2 countries.

Michael D WestAgeX Therapeutics, Inc., Alameda, CA, USA.
Ivan LabatAgeX Therapeutics, Inc., Alameda, CA, USA.
Hal SternbergAgeX Therapeutics, Inc., Alameda, CA, USA.
Dana LaroccaAgeX Therapeutics, Inc., Alameda, CA, USA.
Igor NasonkinBioTime, Inc., Alameda, CA, USA.
Karen B ChapmanJohns Hopkins University, Baltimore, MD, USA.
Ratnesh SinghBioTime, Inc., Alameda, CA, USA.
Eugene MakarevPharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, MD, USA.
Alex AliperPharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, MD, USA.
Andrey KazennovPharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, MD, USA.
Andrey AlekseenkoPharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, MD, USA.
Nikolai ShuvalovPharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, MD, USA.
Evgenia CheskidovaPharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, MD, USA.
Aleksandr AlekseevPharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, MD, USA.
Artem ArtemovPharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, MD, USA.
Evgeny PutinPharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, MD, USA.
Polina MamoshinaPharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, MD, USA.
Nikita PryanichnikovPharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, MD, USA.
Jacob LaroccaAgeX Therapeutics, Inc., Alameda, CA, USA.
Karen CopelandBoulder Statistics, Boulder, CO, USA.
Evgeny IzumchenkoJohns Hopkins University, School of Medicine, Department of Otolaryngology-Head and Neck Cancer Research, Baltimore, MD, USA.
Mikhail KorzinkinPharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, MD, USA.
Alex ZhavoronkovPharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, MD, USA.
Johns Hopkins University · USLineage Cell Therapeutics (United States) · USMoscow Institute of Physics and Technology · RUInnopolis University · RUUniversity of Colorado Boulder · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Here we present the application of deep neural network (DNN) ensembles trained on transcriptomic data to identify the novel markers associated with the mammalian embryonic-fetal transition (EFT). Molecular markers of this process could provide important insights into regulatory mechanisms of normal development, epimorphic tissue regeneration and cancer. Subsequent analysis of the most significant genes behind the DNNs classifier on an independent dataset of adult-derived and human embryonic stem cell (hESC)-derived progenitor cell lines led to the identification of

Indexed as

cancer markerdeep neural networkembryonic-fetal transitionstem cellsWarburg effect

Identifiers

PMID29487692
PMCPMC5814259
OpenAlexW2780040900

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.