Literature DB >> 22142339

Using the reconstructed genome-scale human metabolic network to study physiology and pathology.

A Bordbar1, B O Palsson.   

Abstract

Metabolism plays a key role in many major human diseases. Generation of high-throughput omics data has ushered in a new era of systems biology. Genome-scale metabolic network reconstructions provide a platform to interpret omics data in a biochemically meaningful manner. The release of the global human metabolic network, Recon 1, in 2007 has enabled new systems biology approaches to study human physiology, pathology and pharmacology. There are currently more than 20 publications that utilize Recon 1, including studies of cancer, diabetes, host-pathogen interactions, heritable metabolic disorders and off-target drug binding effects. In this mini-review, we focus on the reconstruction of the global human metabolic network and four classes of its application. We show that computational simulations for numerous pathologies have yielded clinically relevant results, many corroborated by existing or newly generated experimental data.
© 2011 The Association for the Publication of the Journal of Internal Medicine.

Entities:  

Mesh:

Year:  2012        PMID: 22142339      PMCID: PMC3243107          DOI: 10.1111/j.1365-2796.2011.02494.x

Source DB:  PubMed          Journal:  J Intern Med        ISSN: 0954-6820            Impact factor:   8.989


  74 in total

1.  ExPASy: The proteomics server for in-depth protein knowledge and analysis.

Authors:  Elisabeth Gasteiger; Alexandre Gattiker; Christine Hoogland; Ivan Ivanyi; Ron D Appel; Amos Bairoch
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

2.  What is flux balance analysis?

Authors:  Jeffrey D Orth; Ines Thiele; Bernhard Ø Palsson
Journal:  Nat Biotechnol       Date:  2010-03       Impact factor: 54.908

3.  Genome-scale modeling and in silico analysis of mouse cell metabolic network.

Authors:  Suresh Selvarasu; Iftekhar A Karimi; Ghi-Hoon Ghim; Dong-Yup Lee
Journal:  Mol Biosyst       Date:  2009-09-02

4.  A protocol for generating a high-quality genome-scale metabolic reconstruction.

Authors:  Ines Thiele; Bernhard Ø Palsson
Journal:  Nat Protoc       Date:  2010-01-07       Impact factor: 13.491

5.  Metabolic network topology reveals transcriptional regulatory signatures of type 2 diabetes.

Authors:  Aleksej Zelezniak; Tune H Pers; Simão Soares; Mary Elizabeth Patti; Kiran Raosaheb Patil
Journal:  PLoS Comput Biol       Date:  2010-04-01       Impact factor: 4.475

6.  Metabolic modeling and analysis of the metabolic switch in Streptomyces coelicolor.

Authors:  Mohammad T Alam; Maria E Merlo; David A Hodgson; Elizabeth M H Wellington; Eriko Takano; Rainer Breitling
Journal:  BMC Genomics       Date:  2010-03-26       Impact factor: 3.969

7.  Interpreting metabolomic profiles using unbiased pathway models.

Authors:  Rahul C Deo; Luke Hunter; Gregory D Lewis; Guillaume Pare; Ramachandran S Vasan; Daniel Chasman; Thomas J Wang; Robert E Gerszten; Frederick P Roth
Journal:  PLoS Comput Biol       Date:  2010-02-26       Impact factor: 4.475

8.  Reconstruction annotation jamborees: a community approach to systems biology.

Authors:  Ines Thiele; Bernhard Ø Palsson
Journal:  Mol Syst Biol       Date:  2010-04-13       Impact factor: 11.429

9.  KEGG for representation and analysis of molecular networks involving diseases and drugs.

Authors:  Minoru Kanehisa; Susumu Goto; Miho Furumichi; Mao Tanabe; Mika Hirakawa
Journal:  Nucleic Acids Res       Date:  2009-10-30       Impact factor: 16.971

10.  An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR).

Authors:  Jennifer L Reed; Thuy D Vo; Christophe H Schilling; Bernhard O Palsson
Journal:  Genome Biol       Date:  2003-08-28       Impact factor: 13.583

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  41 in total

1.  GIM3E: condition-specific models of cellular metabolism developed from metabolomics and expression data.

Authors:  Brian J Schmidt; Ali Ebrahim; Thomas O Metz; Joshua N Adkins; Bernhard Ø Palsson; Daniel R Hyduke
Journal:  Bioinformatics       Date:  2013-08-23       Impact factor: 6.937

2.  Reconstruction and validation of a constraint-based metabolic network model for bone marrow-derived mesenchymal stem cells.

Authors:  H Fouladiha; S-A Marashi; M A Shokrgozar
Journal:  Cell Prolif       Date:  2015-07-01       Impact factor: 6.831

3.  Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN.

Authors:  Maria Masid; Meric Ataman; Vassily Hatzimanikatis
Journal:  Nat Commun       Date:  2020-06-04       Impact factor: 14.919

Review 4.  Mechanistic systems modeling to guide drug discovery and development.

Authors:  Brian J Schmidt; Jason A Papin; Cynthia J Musante
Journal:  Drug Discov Today       Date:  2012-09-19       Impact factor: 7.851

5.  An Organic Anion Transporter 1 (OAT1)-centered Metabolic Network.

Authors:  Henry C Liu; Neema Jamshidi; Yuchen Chen; Satish A Eraly; Sai Yee Cho; Vibha Bhatnagar; Wei Wu; Kevin T Bush; Ruben Abagyan; Bernhard O Palsson; Sanjay K Nigam
Journal:  J Biol Chem       Date:  2016-07-20       Impact factor: 5.157

6.  IDENTIFYING CANCER SPECIFIC METABOLIC SIGNATURES USING CONSTRAINT-BASED MODELS.

Authors:  A Schultz; S Mehta; C W Hu; F W Hoff; T M Horton; S M Kornblau; A A Qutub
Journal:  Pac Symp Biocomput       Date:  2017

7.  Proliferation inhibition of cisplatin-resistant ovarian cancer cells using drugs screened by integrating a metabolic model and transcriptomic data.

Authors:  E Motamedian; E Taheri; F Bagheri
Journal:  Cell Prolif       Date:  2017-09-03       Impact factor: 6.831

Review 8.  Endothelial Cell Metabolism.

Authors:  Guy Eelen; Pauline de Zeeuw; Lucas Treps; Ulrike Harjes; Brian W Wong; Peter Carmeliet
Journal:  Physiol Rev       Date:  2018-01-01       Impact factor: 37.312

9.  A community-driven global reconstruction of human metabolism.

Authors:  Ines Thiele; Neil Swainston; Ronan M T Fleming; Andreas Hoppe; Swagatika Sahoo; Maike K Aurich; Hulda Haraldsdottir; Monica L Mo; Ottar Rolfsson; Miranda D Stobbe; Stefan G Thorleifsson; Rasmus Agren; Christian Bölling; Sergio Bordel; Arvind K Chavali; Paul Dobson; Warwick B Dunn; Lukas Endler; David Hala; Michael Hucka; Duncan Hull; Daniel Jameson; Neema Jamshidi; Jon J Jonsson; Nick Juty; Sarah Keating; Intawat Nookaew; Nicolas Le Novère; Naglis Malys; Alexander Mazein; Jason A Papin; Nathan D Price; Evgeni Selkov; Martin I Sigurdsson; Evangelos Simeonidis; Nikolaus Sonnenschein; Kieran Smallbone; Anatoly Sorokin; Johannes H G M van Beek; Dieter Weichart; Igor Goryanin; Jens Nielsen; Hans V Westerhoff; Douglas B Kell; Pedro Mendes; Bernhard Ø Palsson
Journal:  Nat Biotechnol       Date:  2013-03-03       Impact factor: 54.908

10.  Using networks to measure similarity between genes: association index selection.

Authors:  Juan I Fuxman Bass; Alos Diallo; Justin Nelson; Juan M Soto; Chad L Myers; Albertha J M Walhout
Journal:  Nat Methods       Date:  2013-12       Impact factor: 28.547

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