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Authors: Sofia Agostinho 1 ; 2 ; 3 ; Joaquim Cabral 1 ; 3 ; 4 ; Ana Fred 1 ; 2 and Carlos Rodrigues 1 ; 3 ; 4

Affiliations: 1 Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal ; 2 Instituto de Telecomunicações (IT), Lisbon, Portugal ; 3 iBB —Institute for Bioengineering and Biosciences, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal ; 4 Associate Laboratory i4HB – Institute for Health and Bioeconomy at Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal

Keyword(s): Cardiac Differentiation, Unsupervised Machine Learning, Whole Transcriptome Visualization, Differentiation Time Mapping.

Abstract: This paper presents a reanalysis, of a previously published RNA-seq dataset, using several unsupervised learning algorithms to study, from a whole transcriptome point of view, the changes occurring during stem cell cardiac differentiation. The main objectives of this work were to highlight differences in gene expression patterns between differentiation stages and, to create a strategy to map bulk RNA-seq samples onto a pseudotime axis to analyse, quantitatively, how the transcriptome is evolving in comparison to the real culture time. The method here proposed effectively portrayed the transcriptomic changes that occurred throughout the differentiation processes, with a visual representation of the entire transcriptome. The portraits revealed over-expressed genes correlated with different biological processes and gene sets for each stage of the differentiation. The time mapping results highlighted not only the abrupt changes in the transcriptome due to the activation and inhibition of the Wnt signalling pathway, but also the fact that upon the effect of the Wnt inhibitor, and despite the additional culture days, the transcriptome is not changing as fast as previously posing questions regarding maturation strategies. Taken together the proposed workflow, was considered promising as a tool to compare different differentiation protocols and maturation strategies. (More)

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Paper citation in several formats:
Agostinho, S.; Cabral, J.; Fred, A. and Rodrigues, C. (2023). Unsupervised Cardiac Differentiation Stage Portraying and Pseudotime Mapping Based on Gene Expression Data. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - BIOINFORMATICS; ISBN 978-989-758-631-6; ISSN 2184-4305, SciTePress, pages 109-120. DOI: 10.5220/0011892200003414

@conference{bioinformatics23,
author={Sofia Agostinho. and Joaquim Cabral. and Ana Fred. and Carlos Rodrigues.},
title={Unsupervised Cardiac Differentiation Stage Portraying and Pseudotime Mapping Based on Gene Expression Data},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - BIOINFORMATICS},
year={2023},
pages={109-120},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011892200003414},
isbn={978-989-758-631-6},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - BIOINFORMATICS
TI - Unsupervised Cardiac Differentiation Stage Portraying and Pseudotime Mapping Based on Gene Expression Data
SN - 978-989-758-631-6
IS - 2184-4305
AU - Agostinho, S.
AU - Cabral, J.
AU - Fred, A.
AU - Rodrigues, C.
PY - 2023
SP - 109
EP - 120
DO - 10.5220/0011892200003414
PB - SciTePress