DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification

dc.contributor.author
Decamps, Clémentine
dc.contributor.author
Arnaud, Alexis
dc.contributor.author
Petitprez, Florent
dc.contributor.author
Ayadi, Mira
dc.contributor.author
Baurès, Aurélia
dc.contributor.author
Armenoult, Lucile
dc.contributor.author
Escalera Guerrero, Sergio
dc.contributor.author
Guyon, Isabelle
dc.contributor.author
Nicolle, Rémy
dc.contributor.author
Tomasini, Richard
dc.contributor.author
Reyniès, Aurélien de
dc.contributor.author
Cros, Jérôme
dc.contributor.author
Blum, Yuna
dc.contributor.author
Richard, Magali
dc.date.issued
2022-03-14T09:36:21Z
dc.date.issued
2022-03-14T09:36:21Z
dc.date.issued
2021-10-02
dc.date.issued
2022-03-14T09:36:22Z
dc.identifier
1471-2105
dc.identifier
https://hdl.handle.net/2445/184089
dc.identifier
714544
dc.description.abstract
Quantifcation of tumor heterogeneity is essential to better understand cancer progression and to adapt therapeutic treatments to patient specifcities. Bioinformatic tools to assess the diferent cell populations from single-omic datasets as bulk transcriptome or methylome samples have been recently developed, including reference-based and reference-free methods. Improved methods using multi-omic datasets are yet to be developed in the future and the community would need systematic tools to perform a comparative evaluation of these algorithms on controlled data.
dc.format
application/pdf
dc.format
application/pdf
dc.language
eng
dc.publisher
BioMed Central
dc.relation
Reproducció del document publicat a: https://doi.org/10.1186/s12859-021-04381-4
dc.relation
BMC Bioinformatics, 2021, vol. 2021, num. 22
dc.relation
https://doi.org/10.1186/s12859-021-04381-4
dc.relation
info:eu-repo/grantAgreement/EC/H2020/826121/EU//iPC
dc.rights
cc-by (c) Decamps, Clémentine et al., 2021
dc.rights
https://creativecommons.org/licenses/by/4.0/
dc.rights
info:eu-repo/semantics/openAccess
dc.source
Articles publicats en revistes (Matemàtiques i Informàtica)
dc.subject
Càncer
dc.subject
Classificació de tumors
dc.subject
Algorismes computacionals
dc.subject
Cancer
dc.subject
Tumors classification
dc.subject
Computer algorithms
dc.title
DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification
dc.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/publishedVersion


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