Diabetes; Metabolic diseases; Networks; Modeling and Simulation; Biochemistry, Genetics and Molecular Biology (all); Drug Discovery; Computer Science Applications; Applied Mathematics
Résumé :
[en] Metabolic diseases (MD) are amenable to network-based modeling frameworks, given the systemic perturbations induced by disrupted molecular mechanisms. We present here a brief overview of network modeling methods applied to inborn errors of metabolism (IEM), systemic metabolic conditions (mainly diabetes), and metabolism-related inflammation and autoimmune disorders. Clinical diagnosis and identification of causal agents in IEMs and uncovering the multifactorial mechanisms underlying the development of diabetes and other systemic metabolic diseases are the main challenges being addressed. The review also highlights some of the studies undertaken to investigate the role of the gut microbiome in MD, especially in diabetes. While the network frameworks employed in different modeling approaches have provided novel insights, some technique-specific limitations and overall gaps in general research trends need further attention.
Précision sur le type de document :
Compte rendu
Disciplines :
Sciences du vivant: Multidisciplinaire, généralités & autres
Auteur, co-auteur :
BADKAS, Apurva ; University of Luxembourg > Faculty of Science, Technology and Medicine > Department of Life Sciences and Medicine > Team Thomas SAUTER
Pacheco, Maria Pires; Department of Life Sciences and Medicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
SAUTER, Thomas ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)
Co-auteurs externes :
no
Langue du document :
Anglais
Titre :
Network modeling approaches for metabolic diseases and diabetes
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