Evidence map›Paper›PMID 37131773›Full record

ArticlebioRxiv : the preprint server for biology2023

Matrisome AnalyzeR: A suite of tools to annotate and quantify ECM molecules in big datasets across organisms.

Petar B Petrov, James M Considine, Valerio Izzi, Alexandra Naba

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Petar B PetrovInfotech Institute, University of Oulu, FI-90014 Oulu, Finland.
James M ConsidineDepartment of Physiology and Biophysics, University of Illinois Chicago, Chicago, IL 60612, USA.
Valerio IzziFaculty of Biochemistry and Molecular Medicine & Faculty of Medicine, BioIM Unit, University of Oulu, FI-90014 Oulu, Finland.
Alexandra NabaDepartment of Physiology and Biophysics, University of Illinois Chicago, Chicago, IL 60612, USA.

Funding

Thinking outside the cell: Leveraging HuBMAP data to build the human ECM atlasU01HG012680 · NHGRI · UNIVERSITY OF ILLINOIS AT CHICAGO · PI GAO, YU, NABA, ALEXANDRA · 2022 to 2025
$2.0M
Enhanced mass-spectrometry-based approaches for in-depth profiling of the cancer extracellular matrixR21CA261642 · NCI · UNIVERSITY OF ILLINOIS AT CHICAGO · PI GAO, YU, NABA, ALEXANDRA · 2022 to 2024
$553k
NCI NIH HHS R21 CA261642NHGRI NIH HHS U01 HG012680
6 · The paper itself

Abstract

The extracellular matrix (ECM) is a complex meshwork of proteins that forms the scaffold of all tissues in multicellular organisms. It plays critical roles in all aspects of life: from orchestrating cell migration during development, to supporting tissue repair. It also plays critical roles in the etiology or progression of diseases. To study this compartment, we defined the compendium of all genes encoding ECM and ECM-associated proteins for multiple organisms. We termed this compendium the "matrisome" and further classified matrisome components into different structural or functional categories. This nomenclature is now largely adopted by the research community to annotate -omics datasets and has contributed to advance both fundamental and translational ECM research. Here, we report the development of Matrisome AnalyzeR, a suite of tools including a web-based application ( https://sites.google.com/uic.edu/matrisome/tools/matrisome-analyzer ) and an R package ( https://github.com/Matrisome/MatrisomeAnalyzeR ). The web application can be used by anyone interested in annotating, classifying, and tabulating matrisome molecules in large datasets without requiring programming knowledge. The companion R package is available to more experienced users, interested in processing larger datasets or in additional data visualization options. SUMMARY STATEMENT: Matrisome AnalyzeR is a suite of tools, including a web-based app and an R package, designed to facilitate the annotation and quantification of extracellular matrix components in big datasets.

Identifiers

PMID37131773
PMCPMC10153148

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.