Simulation and Reconstruction of Metabolite–Metabolite Association Networks Using a Metabolic Dynamic Model and Correlation Based Algorithms

• Published in: Journal of proteome research Vol. 18; no. 3; pp. 1099 - 1113
• Main Authors: Jahagirdar, Sanjeevan, Suarez-Diez, Maria, Saccenti, Edoardo
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 01.03.2019
• Subjects: Algorithms; arachidonic acid; biochemical pathways; biological properties and phenomena; Computer Simulation; dynamic models; Humans; Metabolic Networks and Pathways - genetics; metabolism; metabolites; Metabolome - genetics; metabolomics; Metabolomics - statistics & numerical data; Models, Biological; proteome; Sample Size; Systeem en Synthetische Biologie; Systems and Synthetic Biology; VLAG; arachidonic acid; network inference; arachidonic acid metabolism; top-down approach; metabolic modeling

Biological networks play a paramount role in our understanding of complex biological phenomena, and metabolite–metabolite association networks are now commonly used in metabolomics applications. In this study we evaluate the performance of several network inference algorithms (PCLRC, MRNET, GENIE3,...