scholarly journals A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology

2008 ◽  
Vol 26 (10) ◽  
pp. 1155-1160 ◽  
Author(s):  
Markus J Herrgård ◽  
Neil Swainston ◽  
Paul Dobson ◽  
Warwick B Dunn ◽  
K Yalçin Arga ◽  
...  
Keyword(s):  
Systems Biology ◽  
Metabolic Network ◽  
Network Reconstruction ◽  
Metabolic Network Reconstruction ◽  
Community Approach

scholarly journals Novel Plasmodium falciparum metabolic network reconstruction identifies shifts associated with clinical antimalarial resistance

2017 ◽  
Author(s):  
Maureen A. Carey ◽  
Jason A. Papin ◽  
Jennifer L. Guler
Keyword(s):  
Systems Biology ◽  
Metabolic Network ◽  
Drug Targets ◽  
Artemisinin Resistance ◽  
Network Reconstruction ◽  
Asexual Blood Stage ◽  
Metabolic Network Reconstruction ◽  
Public Health Burden ◽  
Candidate Drug ◽  
Antimalarial Resistance

ABSTRACTBACKGROUNDMalaria remains a major public health burden and resistance has emerged to every antimalarial on the market, including the frontline drug artemisinin. Our limited understanding of Plasmodium biology hinders the elucidation of resistance mechanisms. In this regard, systems biology approaches can facilitate the integration of existing experimental knowledge and further understanding of these mechanisms.RESULTSHere, we developed a novel genome-scale metabolic network reconstruction, iPfal17, of the asexual blood-stage P. falciparum parasite to expand our understanding of metabolic changes that support resistance. We identified 11 metabolic tasks to evaluate iPfal17 performance. Flux balance analysis and simulation of gene knockouts and enzyme inhibition predict candidate drug targets unique to resistant parasites. Moreover, integration of clinical parasite transcriptomes into the iPfal17 reconstruction reveals patterns associated with antimalarial resistance. These results predict that artemisinin sensitive and resistant parasites differentially utilize scavenging and biosynthetic pathways for multiple essential metabolites including folate and polyamines, and others within the mitochondria. Our findings are consistent with experimental literature, while generating novel hypotheses about artemisinin resistance and parasite biology. We detect evidence that resistance parasites maintain greater metabolic flexibility, perhaps representing an incomplete transition to the metabolic state most appropriate for nutrient-rich blood.CONCLUSIONUsing this systems biology approach, we identify metabolic shifts that arise with or in support of the resistant phenotype. This perspective allows us to more productively analyze and interpret clinical expression data for the identification of candidate drug targets for the treatment of resistant parasites.

scholarly journals A genome‐scale metabolic network reconstruction of tomato ( Solanum lycopersicum L.) and its application to photorespiratory metabolism

2016 ◽  
Vol 85 (2) ◽  
pp. 289-304 ◽  
Author(s):  
Huili Yuan ◽  
C.Y. Maurice Cheung ◽  
Mark G. Poolman ◽  
Peter A. J. Hilbers ◽  
Natal A. W. Riel
Keyword(s):  
Metabolic Network ◽  
Solanum Lycopersicum ◽  
Network Reconstruction ◽  
Metabolic Network Reconstruction ◽  
Solanum Lycopersicum L ◽  
A Genome ◽  
Genome Scale

scholarly journals RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor

2018 ◽  
Vol 14 (10) ◽  
pp. e1006541 ◽  
Author(s):  
Hao Wang ◽  
Simonas Marcišauskas ◽  
Benjamín J. Sánchez ◽  
Iván Domenzain ◽  
Daniel Hermansson ◽  
...  
Keyword(s):  
Metabolic Network ◽  
Streptomyces Coelicolor ◽  
Network Reconstruction ◽  
Metabolic Network Reconstruction

scholarly journals mmnet: An R Package for Metagenomics Systems Biology Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-5 ◽  
Author(s):  
Yang Cao ◽  
Xiaofei Zheng ◽  
Fei Li ◽  
Xiaochen Bo
Keyword(s):  
Metabolic Network ◽  
Human Microbiome ◽  
R Package ◽  
Network Reconstruction ◽  
Community Level ◽  
System Level ◽  
Metagenomic Data ◽  
Pure Species ◽  
Integrated Network ◽  
Metabolic Network Reconstruction

The human microbiome plays important roles in human health and disease. Previous microbiome studies focused mainly on single pure species function and overlooked the interactions in the complex communities on system-level. A metagenomic approach introduced recently integrates metagenomic data with community-level metabolic network modeling, but no comprehensive tool was available for such kind of approaches. To facilitate these kinds of studies, we developed an R package,mmnet, to implement community-level metabolic network reconstruction. The package also implements a set of functions for automatic analysis pipeline construction including functional annotation of metagenomic reads, abundance estimation of enzymatic genes, community-level metabolic network reconstruction, and integrated network analysis. The result can be represented in an intuitive way and sent to Cytoscape for further exploration. The package has substantial potentials in metagenomic studies that focus on identifying system-level variations of human microbiome associated with disease.

scholarly journals A simplified metabolic network reconstruction to promote understanding and development of flux balance analysis tools

2019 ◽  
Vol 105 ◽  
pp. 64-71 ◽  
Author(s):  
Kristopher D. Rawls ◽  
Bonnie V. Dougherty ◽  
Edik M. Blais ◽  
Ethan Stancliffe ◽  
Glynis L. Kolling ◽  
...  
Keyword(s):  
Metabolic Network ◽  
Flux Balance Analysis ◽  
Network Reconstruction ◽  
Metabolic Network Reconstruction ◽  
Flux Balance ◽  
Analysis Tools ◽  
Balance Analysis

scholarly journals The Edinburgh human metabolic network reconstruction and its functional analysis

2007 ◽  
Vol 3 (1) ◽  
pp. 135 ◽  
Author(s):  
Hongwu Ma ◽  
Anatoly Sorokin ◽  
Alexander Mazein ◽  
Alex Selkov ◽  
Evgeni Selkov ◽  
...  
Keyword(s):  
Functional Analysis ◽  
Metabolic Network ◽  
Network Reconstruction ◽  
Metabolic Network Reconstruction

scholarly journals Metabolic network reconstruction of Chlamydomonas offers insight into light‐driven algal metabolism

2011 ◽  
Vol 7 (1) ◽  
pp. 518 ◽  
Author(s):  
Roger L Chang ◽  
Lila Ghamsari ◽  
Ani Manichaikul ◽  
Erik F Y Hom ◽  
Santhanam Balaji ◽  
...  
Keyword(s):  
Metabolic Network ◽  
Network Reconstruction ◽  
Metabolic Network Reconstruction ◽  
Algal Metabolism ◽  
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