Matrisome AnalyzeR - a suite of tools to annotate and quantify ECM molecules in big datasets across organisms
Approved
Classifications
MinEdu publication type
A1 Journal article (peer-reviewed)
Definition
Article
Target group
Scientific
Peer reviewed
Peer-reviewed
Article type
Journal article
Host publication type
Journal
Publication channel information
Title of journal/series
Journal of cell science
ISSN (print)
0021-9533
ISSN (electronic)
1477-9137
ISSN (linking)
0021-9533
Publisher
Company of Biologists Ltd
Publication forum ID
59827
Publication forum level
2
Country of publication
United Kingdom
Internationality
Yes
Detailed publication information
Publication year
2023
Reporting year
2023
Journal/series volume number
136
Journal/series issue number
17
DOI
10.1242/jcs.261255
Language of publication
English
Co-publication information
International co-publication
Yes
Co-publication with a company
No
Availability
Link to online publication
Link to self-archived version
Classification and additional information
MinEdu field of science classification
1182 Biochemistry, cell and molecular biology
Keywords
Bioinformatics; Data annotation; Extracellular matrix; Model organisms; Omics
Funding information
Funding information in the publication
This work was supported in part by the National Institutes of Health (U01HG012680, R21CA261642 and R01CA232517 to A.N.) and by a start-up fund from the Department of Physiology and Biophysics of the University of Illinois Chicago (A.N.). This research is connected to the DigiHealth-project, a strategic profiling project at the University of Oulu (V.I.) and the Infotech Institute (V.I., P.B.P.). The project is supported by the Academy of Finland (DECISION 326291 to V.I.), the Cancer Foundation Finland (V.I.), the Finnish Cancer Institute, and K. Albin Johansson Cancer Research Fellowship fund (V.I.). Open Access funding provided by National Institutes of Health. Deposited in PMC for immediate release.
Source database ID
Scopus ID
2-s2.0-85169715368
Other database ID
PMID: 37555624