Evidence map›Paper›PMID 38938656›Full record

ArticleIn silico plants2023

Graph metric learning quantifies morphological differences between two genotypes of shoot apical meristem cells in

Cory Braker Scott, Eric Mjolsness, Diane Oyen, Chie Kodera, Magalie Uyttewaal, David Bouchez

Abstract read
In one paragraph

Article in In silico plants, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. A transient radial cortical microtubule array primes cell division inProceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  2. 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

6 authors.

Cory Braker ScottDepartment of Mathematics and Computer Science, Colorado College, Colorado Springs, CO 80903, USA.ORCID 0000-0002-5561-2368
Eric MjolsnessDepartment of Computer Science, University of California Irvine, Irvine, CA 92697, USA.
Diane OyenLos Alamos National Laboratory, Los Alamos, NM 87544, USA.
Chie KoderaUniversité Paris-Saclay, INRAE, AgroParisTech, Institut Jean-Pierre Bourgin (IJPB), 78000 Versailles, France.
Magalie UyttewaalUniversité Paris-Saclay, INRAE, AgroParisTech, Institut Jean-Pierre Bourgin (IJPB), 78000 Versailles, France.ORCID 0000-0003-2881-6637
David BouchezUniversité Paris-Saclay, INRAE, AgroParisTech, Institut Jean-Pierre Bourgin (IJPB), 78000 Versailles, France.

Funding

Multiscale theory of synapse function with model reduction by machine learningRF1DA055668 · NIDA · UNIVERSITY OF CALIFORNIA-IRVINE · PI MJOLSNESS, ERIC D · 2021 to 2021
$1.1M
Machine Learning for Generalized Multiscale ModelingR56AG059602 · NIA · UNIVERSITY OF CALIFORNIA-IRVINE · PI MJOLSNESS, ERIC D · 2018 to 2018
$619k
NIA NIH HHS R56 AG059602NIDA NIH HHS RF1 DA055668
6 · The paper itself

Abstract

We present a method for learning 'spectrally descriptive' edge weights for graphs. We generalize a previously known distance measure on graphs (graph diffusion distance [GDD]), thereby allowing it to be tuned to minimize an arbitrary loss function. Because all steps involved in calculating this modified GDD are differentiable, we demonstrate that it is possible for a small neural network model to learn edge weights which minimize loss. We apply this method to discriminate between graphs constructed from shoot apical meristem images of two genotypes of

Indexed as

Cell morphologygraph metricsmorphodynamicsneural networksspectral graph theory

Identifiers

PMID38938656
PMCPMC11210494

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.