TY - JOUR
T1 - Integrating Omics Data in Genome-Scale Metabolic Modeling
T2 - A Methodological Perspective for Precision Medicine
AU - Sen, Partho
AU - Orešič, Matej
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2023/7
Y1 - 2023/7
N2 - Recent advancements in omics technologies have generated a wealth of biological data. Integrating these data within mathematical models is essential to fully leverage their potential. Genome-scale metabolic models (GEMs) provide a robust framework for studying complex biological systems. GEMs have significantly contributed to our understanding of human metabolism, including the intrinsic relationship between the gut microbiome and the host metabolism. In this review, we highlight the contributions of GEMs and discuss the critical challenges that must be overcome to ensure their reproducibility and enhance their prediction accuracy, particularly in the context of precision medicine. We also explore the role of machine learning in addressing these challenges within GEMs. The integration of omics data with GEMs has the potential to lead to new insights, and to advance our understanding of molecular mechanisms in human health and disease.
AB - Recent advancements in omics technologies have generated a wealth of biological data. Integrating these data within mathematical models is essential to fully leverage their potential. Genome-scale metabolic models (GEMs) provide a robust framework for studying complex biological systems. GEMs have significantly contributed to our understanding of human metabolism, including the intrinsic relationship between the gut microbiome and the host metabolism. In this review, we highlight the contributions of GEMs and discuss the critical challenges that must be overcome to ensure their reproducibility and enhance their prediction accuracy, particularly in the context of precision medicine. We also explore the role of machine learning in addressing these challenges within GEMs. The integration of omics data with GEMs has the potential to lead to new insights, and to advance our understanding of molecular mechanisms in human health and disease.
KW - constraint-based modeling
KW - host microbiome
KW - human metabolic networks
KW - human metabolism
KW - metabolic modeling
KW - metabolic reconstructions
KW - multi-omics
KW - constraint-based modeling
KW - multi-omics
KW - metabolic modeling
KW - metabolic reconstructions
KW - human metabolic networks
KW - human metabolism
KW - host microbiome
UR - http://www.scopus.com/inward/record.url?scp=85166249655&partnerID=8YFLogxK
U2 - 10.3390/metabo13070855
DO - 10.3390/metabo13070855
M3 - Review Article or Literature Review
AN - SCOPUS:85166249655
SN - 2218-1989
VL - 13
JO - Metabolites
JF - Metabolites
IS - 7
M1 - 855
ER -