A novel approach for determining the optimal number of independent components for reproducible cancer transcriptomes data analysis

Kairov, U.; Cantini, L.; Greco, A.; Molkenov, A.; Czerwinska, U.; Barillot, E.; Zinovyev, A.

dc.contributor.author	Kairov, U.
dc.contributor.author	Cantini, L.
dc.contributor.author	Greco, A.
dc.contributor.author	Molkenov, A.
dc.contributor.author	Czerwinska, U.
dc.contributor.author	Barillot, E.
dc.contributor.author	Zinovyev, A.
dc.date.accessioned	2017-09-20T04:37:44Z
dc.date.available	2017-09-20T04:37:44Z
dc.date.issued	2017-09-15
dc.identifier.citation	Kairov, U. et al. (2017) A novel approach for determining the optimal number of independent components for reproducible cancer transcriptomes data analysis. National Laboratory Astana, Nazarbayev University	ru_RU
dc.identifier.uri	http://nur.nu.edu.kz/handle/123456789/2635
dc.language.iso	en	ru_RU
dc.publisher	National Laboratory Astana, Nazarbayev University	ru_RU
dc.rights	Open Access - the content is available to the general public	ru_RU
dc.rights	Attribution-NonCommercial-ShareAlike 3.0 United States	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-sa/3.0/us/	*
dc.subject	transcriptome	ru_RU
dc.subject	Independent Component Analysis	ru_RU
dc.subject	reproducibility	ru_RU
dc.subject	cancer	ru_RU
dc.title	A novel approach for determining the optimal number of independent components for reproducible cancer transcriptomes data analysis	ru_RU
dc.type	Abstract	ru_RU