TY - JOUR
T1 - The global evolution and impact of systems biology and artificial intelligence in stem cell research and therapeutics development
T2 - a scoping review
AU - Silva-Sousa, Thayna
AU - Usuda, Júlia Nakanishi
AU - Al-Arawe, Nada
AU - Frias, Francisca
AU - Hinterseher, Irene
AU - Catar, Rusan
AU - Luecht, Christian
AU - Riesner, Katarina
AU - Hackel, Alexander
AU - Schimke, Lena F.
AU - Dias, Haroldo Dutra
AU - Filgueiras, Igor Salerno
AU - Nakaya, Helder I.
AU - Camara, Niels Olsen Saraiva
AU - Fischer, Stefan
AU - Riemekasten, Gabriela
AU - Ringdén, Olle
AU - Penack, Olaf
AU - Winkler, Tobias
AU - Duda, Georg
AU - Fonseca, Dennyson Leandro M.
AU - Cabral-Marques, Otávio
AU - Moll, Guido
N1 - Publisher Copyright:
© The Author(s) 2024. Published by Oxford University Press. All rights reserved.
PY - 2024/11/1
Y1 - 2024/11/1
N2 - Advanced bioinformatics analysis, such as systems biology (SysBio) and artificial intelligence (AI) approaches, including machine learning (ML) and deep learning (DL), is increasingly present in stem cell (SC) research. An approximate timeline on these developments and their global impact is still lacking. We conducted a scoping review on the contribution of SysBio and AI analysis to SC research and therapy development based on literature published in PubMed between 2000 and 2024. We identified an 8 to 10-fold increase in research output related to all 3 search terms between 2000 and 2021, with a 10-fold increase in AI-related production since 2010. Use of SysBio and AI still predominates in preclinical basic research with increasing use in clinically oriented translational medicine since 2010. SysBio- and AI-related research was found all over the globe, with SysBio output led by the (US, n = 1487), (UK, n = 1094), Germany (n = 355), The Netherlands (n = 339), Russia (n = 215), and France (n = 149), while for AI-related research the US (n = 853) and UK (n = 258) take a strong lead, followed by Switzerland (n = 69), The Netherlands (n = 37), and Germany (n = 19). The US and UK are most active in SCs publications related to AI/ML and AI/DL. The prominent use of SysBio in ESC research was recently overtaken by prominent use of AI in iPSC and MSC research. This study reveals the global evolution and growing intersection among AI, SysBio, and SC research over the past 2 decades, with substantial growth in all 3 fields and exponential increases in AI-related research in the past decade.
AB - Advanced bioinformatics analysis, such as systems biology (SysBio) and artificial intelligence (AI) approaches, including machine learning (ML) and deep learning (DL), is increasingly present in stem cell (SC) research. An approximate timeline on these developments and their global impact is still lacking. We conducted a scoping review on the contribution of SysBio and AI analysis to SC research and therapy development based on literature published in PubMed between 2000 and 2024. We identified an 8 to 10-fold increase in research output related to all 3 search terms between 2000 and 2021, with a 10-fold increase in AI-related production since 2010. Use of SysBio and AI still predominates in preclinical basic research with increasing use in clinically oriented translational medicine since 2010. SysBio- and AI-related research was found all over the globe, with SysBio output led by the (US, n = 1487), (UK, n = 1094), Germany (n = 355), The Netherlands (n = 339), Russia (n = 215), and France (n = 149), while for AI-related research the US (n = 853) and UK (n = 258) take a strong lead, followed by Switzerland (n = 69), The Netherlands (n = 37), and Germany (n = 19). The US and UK are most active in SCs publications related to AI/ML and AI/DL. The prominent use of SysBio in ESC research was recently overtaken by prominent use of AI in iPSC and MSC research. This study reveals the global evolution and growing intersection among AI, SysBio, and SC research over the past 2 decades, with substantial growth in all 3 fields and exponential increases in AI-related research in the past decade.
UR - http://www.scopus.com/inward/record.url?scp=85208772481&partnerID=8YFLogxK
U2 - 10.1093/stmcls/sxae054
DO - 10.1093/stmcls/sxae054
M3 - Journal articles
C2 - 39230167
AN - SCOPUS:85208772481
SN - 1066-5099
VL - 42
SP - 929
EP - 944
JO - Stem Cells
JF - Stem Cells
IS - 11
ER -
