Independent component analysis of cancer transcriptomes: optimization of parameters and improvement of interpretability

Chepeleva, M.; Kakoichankava, A.; Yatskou, M. M.; Nazarov, P. V.

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Please use this identifier to cite or link to this item: https://elib.bsu.by/handle/123456789/248662

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DC Field	Value	Language
dc.contributor.author	Chepeleva, M.	-
dc.contributor.author	Kakoichankava, A.	-
dc.contributor.author	Yatskou, M. M.	-
dc.contributor.author	Nazarov, P. V.	-
dc.date.accessioned	2020-09-24T12:32:42Z	-
dc.date.available	2020-09-24T12:32:42Z	-
dc.date.issued	2020	-
dc.identifier.citation	Компьютерные технологии и анализ данных (CTDA’2020) : материалы II Междунар. науч.-практ. конф., Минск, 23–24 апр. 2020 г. / Белорус. гос. ун-т ; редкол.: В. В. Скакун (отв. ред.) [и др.]. – Минск : БГУ, 2020. – С. 170-173.	-
dc.identifier.isbn	978-985-566-942-6	-
dc.identifier.uri	https://elib.bsu.by/handle/123456789/248662	-
dc.description	Секция «Биоинформатика»	-
dc.description.abstract	Here we estimated the optimal parameters of the independent component analysis method regarding the tasks of identification of glioblastoma and pancreatic cancer subtypes, prediction of patient survival and characterization of active biological processes. Analysis of deconvolution results of bulk and single-cell data allows sharing annotation between highly correlated components and improving interpretability of the results	-
dc.language.iso	en	-
dc.publisher	Минск : БГУ	-
dc.subject	ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетика	-
dc.subject	ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Биология	-
dc.title	Independent component analysis of cancer transcriptomes: optimization of parameters and improvement of interpretability	-
dc.type	conference paper	-
Appears in Collections:	2020. Компьютерные технологии и анализ данных (CTDA’2020)

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