Literature DB >> 26628588

Representation and inference of cellular architecture for metabolic reconstruction and modeling.

Suzanne Paley1, Markus Krummenacker1, Peter D Karp1.   

Abstract

MOTIVATION: Metabolic modeling depends on accurately representing the cellular locations of enzyme-catalyzed and transport reactions. We sought to develop a representation of cellular compartmentation that would accurately capture cellular location information. We further sought a representation that would support automated inference of the cellular compartments present in newly sequenced organisms to speed model development, and that would enable representing the cellular compartments present in multiple cell types within a multicellular organism.
RESULTS: We define the cellular architecture of a unicellular organism, or of a cell type from a multicellular organism, as the collection of cellular components it contains plus the topological relationships among those components. We developed a tool for inferring cellular architectures across many domains of life and extended our Cell Component Ontology to enable representation of the inferred architectures. We provide software for visualizing cellular architectures to verify their correctness and software for editing cellular architectures to modify or correct them. We also developed a representation that records the cellular compartment assignments of reactions with minimal duplication of information.
AVAILABILITY AND IMPLEMENTATION: The Cell Component Ontology is freely available. The Pathway Tools software is freely available for academic research and is available for a fee for commercial use. CONTACT: pkarp@ai.sri.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Mesh:

Year:  2015        PMID: 26628588      PMCID: PMC4907387          DOI: 10.1093/bioinformatics/btv702

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  12 in total

1.  The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models.

Authors:  M Hucka; A Finney; H M Sauro; H Bolouri; J C Doyle; H Kitano; A P Arkin; B J Bornstein; D Bray; A Cornish-Bowden; A A Cuellar; S Dronov; E D Gilles; M Ginkel; V Gor; I I Goryanin; W J Hedley; T C Hodgman; J-H Hofmeyr; P J Hunter; N S Juty; J L Kasberger; A Kremling; U Kummer; N Le Novère; L M Loew; D Lucio; P Mendes; E Minch; E D Mjolsness; Y Nakayama; M R Nelson; P F Nielsen; T Sakurada; J C Schaff; B E Shapiro; T S Shimizu; H D Spence; J Stelling; K Takahashi; M Tomita; J Wagner; J Wang
Journal:  Bioinformatics       Date:  2003-03-01       Impact factor: 6.937

2.  MetaCyc and AraCyc. Metabolic pathway databases for plant research.

Authors:  Peifen Zhang; Hartmut Foerster; Christophe P Tissier; Lukas Mueller; Suzanne Paley; Peter D Karp; Seung Y Rhee
Journal:  Plant Physiol       Date:  2005-05       Impact factor: 8.340

3.  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

4.  The pathway tools pathway prediction algorithm.

Authors:  Peter D Karp; Mario Latendresse; Ron Caspi
Journal:  Stand Genomic Sci       Date:  2011-12-23

5.  EcoCyc: fusing model organism databases with systems biology.

Authors:  Ingrid M Keseler; Amanda Mackie; Martin Peralta-Gil; Alberto Santos-Zavaleta; Socorro Gama-Castro; César Bonavides-Martínez; Carol Fulcher; Araceli M Huerta; Anamika Kothari; Markus Krummenacker; Mario Latendresse; Luis Muñiz-Rascado; Quang Ong; Suzanne Paley; Imke Schröder; Alexander G Shearer; Pallavi Subhraveti; Mike Travers; Deepika Weerasinghe; Verena Weiss; Julio Collado-Vides; Robert P Gunsalus; Ian Paulsen; Peter D Karp
Journal:  Nucleic Acids Res       Date:  2012-11-09       Impact factor: 16.971

6.  Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism.

Authors:  Roger L Chang; Lila Ghamsari; Ani Manichaikul; Erik F Y Hom; Santhanam Balaji; Weiqi Fu; Yun Shen; Tong Hao; Bernhard Ø Palsson; Kourosh Salehi-Ashtiani; Jason A Papin
Journal:  Mol Syst Biol       Date:  2011-08-02       Impact factor: 11.429

7.  Computational prediction of human metabolic pathways from the complete human genome.

Authors:  Pedro Romero; Jonathan Wagg; Michelle L Green; Dale Kaiser; Markus Krummenacker; Peter D Karp
Journal:  Genome Biol       Date:  2004-12-22       Impact factor: 13.583

8.  Version 6 of the consensus yeast metabolic network refines biochemical coverage and improves model performance.

Authors:  Benjamin D Heavner; Kieran Smallbone; Nathan D Price; Larry P Walker
Journal:  Database (Oxford)       Date:  2013-08-09       Impact factor: 3.451

9.  The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases.

Authors:  Ron Caspi; Tomer Altman; Richard Billington; Kate Dreher; Hartmut Foerster; Carol A Fulcher; Timothy A Holland; Ingrid M Keseler; Anamika Kothari; Aya Kubo; Markus Krummenacker; Mario Latendresse; Lukas A Mueller; Quang Ong; Suzanne Paley; Pallavi Subhraveti; Daniel S Weaver; Deepika Weerasinghe; Peifen Zhang; Peter D Karp
Journal:  Nucleic Acids Res       Date:  2013-11-12       Impact factor: 16.971

10.  A genome-scale metabolic flux model of Escherichia coli K-12 derived from the EcoCyc database.

Authors:  Daniel S Weaver; Ingrid M Keseler; Amanda Mackie; Ian T Paulsen; Peter D Karp
Journal:  BMC Syst Biol       Date:  2014-06-30
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