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.accessioned | 2022-03-14T09:36:21Z | |
| dc.date.available | 2022-03-14T09:36:21Z | |
| dc.date.issued | 2021-10-02 | |
| dc.date.updated | 2022-03-14T09:36:22Z | |
| 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.mimetype | application/pdf | |
| dc.identifier.idgrec | 714544 | |
| dc.identifier.issn | 1471-2105 | |
| dc.identifier.uri | https://hdl.handle.net/2445/184089 | |
| dc.language.iso | eng | |
| dc.publisher | BioMed Central | |
| dc.relation.isformatof | Reproducció del document publicat a: https://doi.org/10.1186/s12859-021-04381-4 | |
| dc.relation.ispartof | BMC Bioinformatics, 2021, vol. 2021, num. 22 | |
| dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/826121/EU//iPC | |
| dc.relation.uri | https://doi.org/10.1186/s12859-021-04381-4 | |
| dc.rights | cc-by (c) Decamps, Clémentine et al., 2021 | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.source | Articles publicats en revistes (Matemàtiques i Informàtica) | |
| dc.subject.classification | Càncer | |
| dc.subject.classification | Classificació de tumors | |
| dc.subject.classification | Algorismes computacionals | |
| dc.subject.other | Cancer | |
| dc.subject.other | Tumors classification | |
| dc.subject.other | 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 |
Fitxers
Paquet original
1 - 1 de 1