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https://research.matf.bg.ac.rs/handle/123456789/315
Title: | Prediction of PBMC Cell Types Using scRNAseq Reference Profiles | Authors: | Yang, Luning Zhang, Yihan Mitić, Nenad Keskin, Derin B. Zhang, Guang Lan Chitkushev, Lou Brusic, Vladimir |
Affiliations: | Informatics and Computer Science | Keywords: | 10x SCT;gene expression profiles;pattern recognition;PBMC | Issue Date: | 16-Dec-2020 | Related Publication(s): | Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021 | Abstract: | Single cell transcriptomics enables a high-resolution concurrent measurement of gene expression from tens of thousands of cells. We developed a method for determining standardized profiles from SCT data. We defined 48 data sets from 13 different studies and developed single-cellderived-class' (SCDC) profiles representing multiple classes and subclasses of peripheral blood mononuclear cells (PBMC). We applied pattern recognition analysis by calculating the distance from each query cell to the SCDC profiles (excluding the profiles of the query cells). Classification of cells by pattern recognition showed excellent performance for PBMC that were isolated, but not further processed by cell sorting. |
URI: | https://research.matf.bg.ac.rs/handle/123456789/315 | ISBN: | 9781728162157 | DOI: | 10.1109/BIBM49941.2020.9313410 |
Appears in Collections: | Research outputs |
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