Original title: Machine learning models for quantifying phenotypic signatures of cancer cells based on transcriptomic and epigenomic data
Translated title: Machine learning models for quantifying phenotypic signatures of cancer cells based on transcriptomic and epigenomic data
Authors: Koban, Martin ; PhD, Florian Halbritter, (referee) ; Mehnen, Lars (advisor)
Document type: Master’s theses
Year: 2020
Language: eng
Publisher: Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií
Abstract: [eng] [cze]

Keywords: chromatínová dostupnosť; génová expresia; klasifikácia; metadáta; rakovina; strojové učenie; cancer; chromatin accessibility; classification; gene expression; machine learning; metadata

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/195467

Permalink: http://www.nusl.cz/ntk/nusl-433123


The record appears in these collections:
Universities and colleges > Public universities > Brno University of Technology
Academic theses (ETDs) > Master’s theses
 Record created 2021-02-24, last modified 2022-09-04


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