Literature DB >> 19363119

Gene expression profiling and the use of genome-scale in silico models of Escherichia coli for analysis: providing context for content.

Nathan E Lewis1, Byung-Kwan Cho, Eric M Knight, Bernhard O Palsson.   

Abstract

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Year:  2009        PMID： 19363119      PMCID： PMC2681886          DOI： 10.1128/JB.00034-09

Source DB:  PubMed          Journal:  J Bacteriol        ISSN： 0021-9193            Impact factor:   3.490


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  84 in total

1.  Metabolic gene-deletion strains of Escherichia coli evolve to computationally predicted growth phenotypes.

Authors:  Stephen S Fong; Bernhard Ø Palsson
Journal:  Nat Genet       Date:  2004-09-26       Impact factor: 38.330

2.  Integration of gene expression data into genome-scale metabolic models.

Authors:  Mats Akesson; Jochen Förster; Jens Nielsen
Journal:  Metab Eng       Date:  2004-10       Impact factor: 9.783

Review 3.  Genome-scale models of microbial cells: evaluating the consequences of constraints.

Authors:  Nathan D Price; Jennifer L Reed; Bernhard Ø Palsson
Journal:  Nat Rev Microbiol       Date:  2004-11       Impact factor: 60.633

4.  Investigating metabolite essentiality through genome-scale analysis of Escherichia coli production capabilities.

Authors:  Marcin Imieliński; Călin Belta; Adám Halász; Harvey Rubin
Journal:  Bioinformatics       Date:  2005-01-25       Impact factor: 6.937

5.  Identifying gene targets for the metabolic engineering of lycopene biosynthesis in Escherichia coli.

Authors:  Hal Alper; Yong-Su Jin; J F Moxley; G Stephanopoulos
Journal:  Metab Eng       Date:  2005-05       Impact factor: 9.783

6.  From specific gene regulation to genomic networks: a global analysis of transcriptional regulation in Escherichia coli.

Authors:  D Thieffry; A M Huerta; E Pérez-Rueda; J Collado-Vides
Journal:  Bioessays       Date:  1998-05       Impact factor: 4.345

7.  Systems properties of the Haemophilus influenzae Rd metabolic genotype.

Authors:  J S Edwards; B O Palsson
Journal:  J Biol Chem       Date:  1999-06-18       Impact factor: 5.157

8.  Reconstruction and functional characterization of the human mitochondrial metabolic network based on proteomic and biochemical data.

Authors:  Thuy D Vo; Harvey J Greenberg; Bernhard O Palsson
Journal:  J Biol Chem       Date:  2004-06-17       Impact factor: 5.157

9.  Genome-scale in silico models of E. coli have multiple equivalent phenotypic states: assessment of correlated reaction subsets that comprise network states.

Authors:  Jennifer L Reed; Bernhard Ø Palsson
Journal:  Genome Res       Date:  2004-09       Impact factor: 9.043

10.  New genes implicated in the protection of anaerobically grown Escherichia coli against nitric oxide.

Authors:  Marta C Justino; João B Vicente; Miguel Teixeira; Lígia M Saraiva
Journal:  J Biol Chem       Date:  2004-11-16       Impact factor: 5.157
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  26 in total

1.  Elimination of thermodynamically infeasible loops in steady-state metabolic models.

Authors:  Jan Schellenberger; Nathan E Lewis; Bernhard Ø Palsson
Journal:  Biophys J       Date:  2011-02-02       Impact factor: 4.033

2.  Adaptive evolution of Escherichia coli K-12 MG1655 during growth on a Nonnative carbon source, L-1,2-propanediol.

Authors:  Dae-Hee Lee; Bernhard Ø Palsson
Journal:  Appl Environ Microbiol       Date:  2010-04-30       Impact factor: 4.792

3.  Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities.

Authors:  Xin Fang; Anand Sastry; Nathan Mih; Donghyuk Kim; Justin Tan; James T Yurkovich; Colton J Lloyd; Ye Gao; Laurence Yang; Bernhard O Palsson
Journal:  Proc Natl Acad Sci U S A       Date:  2017-09-05       Impact factor: 11.205

4.  Network context and selection in the evolution to enzyme specificity.

Authors:  Hojung Nam; Nathan E Lewis; Joshua A Lerman; Dae-Hee Lee; Roger L Chang; Donghyuk Kim; Bernhard O Palsson
Journal:  Science       Date:  2012-08-31       Impact factor: 47.728

5.  Identifying radiation exposure biomarkers from mouse blood transcriptome.

Authors:  Daniel R Hyduke; Evagelia C Laiakis; Heng-Hong Li; Albert J Fornace
Journal:  Int J Bioinform Res Appl       Date:  2013

6.  Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models.

Authors:  Nathan E Lewis; Kim K Hixson; Tom M Conrad; Joshua A Lerman; Pep Charusanti; Ashoka D Polpitiya; Joshua N Adkins; Gunnar Schramm; Samuel O Purvine; Daniel Lopez-Ferrer; Karl K Weitz; Roland Eils; Rainer König; Richard D Smith; Bernhard Ø Palsson
Journal:  Mol Syst Biol       Date:  2010-07       Impact factor: 11.429

Review 7.  Studying Salmonellae and Yersiniae host-pathogen interactions using integrated 'omics and modeling.

Authors:  Charles Ansong; Brooke L Deatherage; Daniel Hyduke; Brian Schmidt; Jason E McDermott; Marcus B Jones; Sadhana Chauhan; Pep Charusanti; Young-Mo Kim; Ernesto S Nakayasu; Jie Li; Afshan Kidwai; George Niemann; Roslyn N Brown; Thomas O Metz; Kathleen McAteer; Fred Heffron; Scott N Peterson; Vladimir Motin; Bernhard O Palsson; Richard D Smith; Joshua N Adkins
Journal:  Curr Top Microbiol Immunol       Date:  2013       Impact factor: 4.291

Review 8.  Metabolic systems biology.

Authors:  Bernhard Palsson
Journal:  FEBS Lett       Date:  2009-12-17       Impact factor: 4.124

9.  Systems biology definition of the core proteome of metabolism and expression is consistent with high-throughput data.

Authors:  Laurence Yang; Justin Tan; Edward J O'Brien; Jonathan M Monk; Donghyuk Kim; Howard J Li; Pep Charusanti; Ali Ebrahim; Colton J Lloyd; James T Yurkovich; Bin Du; Andreas Dräger; Alex Thomas; Yuekai Sun; Michael A Saunders; Bernhard O Palsson
Journal:  Proc Natl Acad Sci U S A       Date:  2015-08-10       Impact factor: 11.205

10.  Computational evaluation of cellular metabolic costs successfully predicts genes whose expression is deleterious.

Authors:  Allon Wagner; Raphy Zarecki; Leah Reshef; Camelia Gochev; Rotem Sorek; Uri Gophna; Eytan Ruppin
Journal:  Proc Natl Acad Sci U S A       Date:  2013-11-06       Impact factor: 11.205
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