Weakly-supervised individual human cell classification

dc.contributor.author	Kolinko, Danylo
dc.date.accessioned	2021-09-08T08:30:53Z
dc.date.available	2021-09-08T08:30:53Z
dc.date.issued	2021
dc.identifier.citation	Kolinko, Danylo. Weakly-supervised individual human cell classification: Bachelor Thesis: manuscript / Danylo Kolinko; Supervisor: Igor Krashenyi; Ukrainian Catholic University, Department of Computer Sciences. – Lviv: 2021. – 49 p.: ill.	uk
dc.identifier.uri	https://er.ucu.edu.ua/handle/1/2861
dc.description.abstract	Proteins have an essential role in all cellular processes and greatly determine their functional properties. With the development of microscopy, we have the ability to study localization patterns of proteins within a cell group. Differences in the location among cell populations are called single-cell variability (SCV). SCV accounts for a difference in reactions between cells. Studying this connection may aid the development of treatment for cancer [23]. To this end, we develop a cell classifier trained to determine the correspondence of protein location to cell organelles in a single cell. A classifier is trained with image-level labels, so the training process is weakly supervised.	uk
dc.language.iso	en	uk
dc.subject	proteins	uk
dc.subject	single-cell variability	uk
dc.subject	treatment for cancer	uk
dc.subject	cell classifier	uk
dc.title	Weakly-supervised individual human cell classification	uk
dc.type	Preprint	uk
dc.status	Публікується вперше	uk