Special Issue: New Advances in Bioinformatics and Biomedical Engineering Using Machine Learning Techniques, IWBBIO-2022-Reference-Cited by-同舟云学术

Special Issue: New Advances in Bioinformatics and Biomedical Engineering Using Machine Learning Techniques, IWBBIO-2022

Published:2023-08-01 Issue:8 Volume:14 Page:1574
ISSN:2073-4425
Container-title:Genes
language:en
Short-container-title:Genes

Author:

Valenzuela Olga¹^ORCID,Ortuño Francisco²^ORCID,Benso Alfredo³^ORCID,Schwartz Jean-Marc⁴^ORCID,de Brevern Alexandre G.⁵^ORCID,Rojas Ignacio²^ORCID

Affiliation:

1. Department of Applied Mathematics, University of Granada, 18071 Granada, Spain

2. Department of Computer Architecture and Computer Technology, Information and Communications Technology Centre (CITIC-UGR), University of Granada, 18010 Granada, Spain

3. Systems Biology Group, Dip. Automatica e Informatica, Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy

4. School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester M13 9PT, UK

5. Université de Paris, INSERM, BIGR, F-75014 Paris, France

Abstract

Bioinformatics is revolutionizing Biomedicine in the way we treat and diagnose pathologies related to biological manifestations resulting from variations or mutations of our DNA [...]

Publisher

MDPI AG

Subject

Genetics (clinical),Genetics

Link

https://www.mdpi.com/2073-4425/14/8/1574/pdf

Reference9 articles.

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2. Vasighizaker, A., Trivedi, Y., and Rueda, L. (2023). Cell Type Annotation Model Selection: General-Purpose vs. Pattern-Aware Feature Gene Selection in Single-Cell RNA-Seq Data. Genes, 14.

3. Dobrovolny, M., Benes, J., Langer, J., Krejcar, O., and Selamat, A. (2023). Study on Sperm-Cell Detection Using YOLOv5 Architecture with Labaled Dataset. Genes, 14.

4. Georgieva, O. (2023). An Iterative Unsupervised Method for Gene Expression Differentiation. Genes, 14.

5. Torres-Martos, Á., Bustos-Aibar, M., Ramírez-Mena, A., Cámara-Sánchez, S., Anguita-Ruiz, A., Alcalá, R., Aguilera, C.M., and Alcalá-Fdez, J. (2023). Omics Data Preprocessing for Machine Learning: A Case Study in Childhood Obesity. Genes, 14.