Genome-scale metabolic models in translational medicine: the current status and potential of machine learning in improving the effectiveness of the models-Reference-Cited by-同舟云学术

Genome-scale metabolic models in translational medicine: the current status and potential of machine learning in improving the effectiveness of the models

Published:2024 Issue:4 Volume:20 Page:234-247
ISSN:2515-4184
Container-title:Molecular Omics
language:en
Short-container-title:Mol. Omics

Author:

Turanli Beste¹²,Gulfidan Gizem¹,Aydogan Ozge Onluturk¹,Kula Ceyda¹²,Selvaraj Gurudeeban³⁴^ORCID,Arga Kazim Yalcin¹²⁵^ORCID

Affiliation:

1. Marmara University, Faculty of Engineering, Department of Bioengineering, Istanbul, Turkey

2. Health Biotechnology Joint Research and Application Center of Excellence, Istanbul, Turkey

3. Concordia University, Centre for Research in Molecular Modeling & Department of Chemistry and Biochemistry, Quebec, Canada

4. Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha Dental College and Hospital, Department of Biomaterials, Bioinformatics Unit, Chennai, India

5. Marmara University, Genetic and Metabolic Diseases Research and Investigation Center, Istanbul, Turkey

Abstract

The use of genome scale metabolic models supported by machine learning from bench side to bed side.

Funder

Türkiye Bilimsel ve Teknolojik Araştırma Kurumu

Yükseköğretim Kurulu

Marmara Üniversitesi

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/MO/D3MO00152K

Reference159 articles.

1. An atlas of human metabolism

2. Current status and applications of genome-scale metabolic models

3. Exploring the potential of Saccharomyces cerevisiae for biopharmaceutical protein production

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