The Edinburgh human metabolic network reconstruction and its functional analysis

By Hongwu Ma, Anatoly A. Sorokin, Alexander Mazein, Alexey Selkov, Evgeni Selkov Jr., Oleg V. Demin, Igor Goryanin. Molecular Systems Biology, 2007

470 citations recorded by the source corpus.

A better understanding of human metabolism and its relationship with diseases is an important task in human systems biology studies. In this paper, we present a high‐quality human metabolic network manually reconstructed by integrating genome annotation information from different databases and metabolic reaction information from literature. The network contains nearly 3000 metabolic reactions, which were reorganized into about 70 human‐specific metabolic pathways according to their functional relationships. By analysis of the functional connectivity of the metabolites in the network, the bow‐tie structure, which was found previously by structure analysis, is reconfirmed. Furthermore, the distribution of the disease related genes in the network suggests that the IN (substrates) subset of the bow‐tie structure has more flexibility than other parts.

Subfields: Molecular Biology, Physiology

View Paper: https://www.semanticscholar.org/paper/9166e7ef9f6d06b5092a99b027e11d74a8fcd31e

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Citations in the corpus

Flux balance analysis of biological systems: applications and challenges (2009, background): “Reconstructions of human metabolism have also been reported [43, 44].”
Predicting Network Activity from High Throughput Metabolomics (2013, methodology): “The reference metabolic network model The genome-scale human metabolic network in mummichog is based on KEGG [38], UCSD Recon1 [15] and Edinburgh human metabolic network [16].”
A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology (2008, background): “This is even more problematic in the case of reconstructions of the larger human metabolic network 4,38 .”
Network Medicine: A Network-based Approach to Human Disease (2011, methodology): “An independent manual construction by Ma et al.(125) contains nearly 3,000 metabolic”
Using graph theory to analyze biological networks (2011, background): “Modern sequencing techniques allow the reconstruction of the network of biochemical reactions in many organisms, from bacteria to human [38,39].”
Network-based prediction of human tissue-specific metabolism (2008, background): “Although fundamental steps forward, reconstructions of the global human metabolic network based on an extensive evaluation of genomic and bibliomic data (that is, comprehensive assessment of the literature”
ConsensusPathDB: toward a more complete picture of cell biology (2010, methodology): “The newly integrated data include complex protein interactions from Corum (4), large-scale protein interaction networks from IntAct (5) (designated IntAct-LS), manually curated protein–protein interactions from MIPS-MPPI (6), protein–protein interactions from the Pathogen Interaction Gateway (PIG) m”
Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data (2011, background): “This model includes reactions from the public databases BiGG (H. sapiens Recon 1) [7], the Edinburgh Human Metabolic Network [31] and KEGG PATHWAY [29].”
Cortical High-Density Counterstream Architectures (2013, background): “A core-periphery structure has been observed in other self-organized information-processing architectures, both human-made such as theWorld Wide Web (113) and the Internet (114, 115), and in biological networks, such as in metabolism (116, 117), the immune system (118), and cell signaling (119–121).”
SMPDB: The Small Molecule Pathway Database (2009, background): “Over the past decade, a number of superb, web-accessible molecular pathway resources have emerged, including Kyoto Encyclopedia of Genes and Genomes (KEGG) (5), the ‘Cyc’ databases (6,7), the Reactome database (8), WikiPathways/GeneMAPP (9), the Edinburgh Human Metabolic Network (EHMN) (10), PharmGK”
Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, background): “…that metabolic network data are often still incomplete, and often reflect optimal growth conditions (Edwards & Palsson, 2000a; Forster et al., 2003; Duarte et al., 2007; Ma et al., 2007; Shlomi et al., 2008, 2009; Folger et al., 2011; Holme, 2011; Chavali et al., 2012; Szalay-Bekő et al., 2012).”
An atlas of human metabolism (2020, methodology): “This effort began in earnest with the development of Recon1 (10) and the Edinburgh Human Metabolic Network (EHMN) (11), which served as the starting point for two parallel model series: the Recon series (Recon1, 2, and 3D) (10, 12, 13) and the Human Metabolic Reaction series (HMR1 and 2) (14, 15).”