Multi-omics data integration approaches for precision oncology-Reference-Cited by-同舟云学术

Multi-omics data integration approaches for precision oncology

Published:2022 Issue:6 Volume:18 Page:469-479
ISSN:2515-4184
Container-title:Molecular Omics
language:en
Short-container-title:Mol. Omics

Author:

Correa-Aguila Raidel¹²^ORCID,Alonso-Pupo Niuxia³^ORCID,Hernández-Rodríguez Erix W.⁴^ORCID

Affiliation:

1. Laboratorio de Farmacología Clínica Experimental, Departamento de Docencia e Investigaciones, Instituto Nacional de Oncología y Radiobiología, 10400 La Habana, Cuba

2. Laboratorio de Química Computacional y Teórica, Facultad de Química, Universidad de La Habana, 10400 La Habana, Cuba

3. Departamento de Ciencias Básicas, Facultad de Ciencias Médicas “Manuel Fajardo”, Universidad de Ciencias Médicas de La Habana, 10400 La Habana, Cuba

4. Laboratorio de Bioinformática y Química Computacional (LBQC), Facultad de Medicina, Universidad Católica del Maule, & Escuela de Química y Farmacia, Facultad de Medicina, Universidad Católica del Maule, 3460000 Talca, Chile, 3460000 Talca, Chile

Abstract

A combination of dimensionality reduction techniques, unsupervised and supervised data integration methods with machine learning approaches can be pivotal to extract valuable insights from multi-omics data in the field of precision oncology.

Publisher

Royal Society of Chemistry (RSC)

Subject

Genetics,Molecular Biology,Biochemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2022/MO/D1MO00411E

Reference120 articles.

1. Next-generation sequencing: advances and applications in cancer diagnosis

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