Literature DB >> 21685882

Metabolic engineering: from retrofitting to green field.

Lars K Nielsen.   

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Year:  2011        PMID： 21685882     DOI： 10.1038/nchembio.601

Source DB:  PubMed          Journal:  Nat Chem Biol        ISSN： 1552-4450            Impact factor:   15.040


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  10 in total

1.  Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth.

Authors:  Rafael U Ibarra; Jeremy S Edwards; Bernhard O Palsson
Journal:  Nature       Date:  2002-11-14       Impact factor: 49.962

Review 2.  Metabolic engineering for the microbial production of 1,3-propanediol.

Authors:  Charles E Nakamura; Gregory M Whited
Journal:  Curr Opin Biotechnol       Date:  2003-10       Impact factor: 9.740

3.  Exploring the diversity of complex metabolic networks.

Authors:  Vassily Hatzimanikatis; Chunhui Li; Justin A Ionita; Christopher S Henry; Matthew D Jankowski; Linda J Broadbelt
Journal:  Bioinformatics       Date:  2004-12-21       Impact factor: 6.937

Review 4.  The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli.

Authors:  Adam M Feist; Bernhard Ø Palsson
Journal:  Nat Biotechnol       Date:  2008-06       Impact factor: 54.908

5.  Metabolic engineering of Escherichia coli for direct production of 1,4-butanediol.

Authors:  Harry Yim; Robert Haselbeck; Wei Niu; Catherine Pujol-Baxley; Anthony Burgard; Jeff Boldt; Julia Khandurina; John D Trawick; Robin E Osterhout; Rosary Stephen; Jazell Estadilla; Sy Teisan; H Brett Schreyer; Stefan Andrae; Tae Hoon Yang; Sang Yup Lee; Mark J Burk; Stephen Van Dien
Journal:  Nat Chem Biol       Date:  2011-05-22       Impact factor: 15.040

6.  In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data.

Authors:  J S Edwards; R U Ibarra; B O Palsson
Journal:  Nat Biotechnol       Date:  2001-02       Impact factor: 54.908

7.  Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization.

Authors:  Anthony P Burgard; Priti Pharkya; Costas D Maranas
Journal:  Biotechnol Bioeng       Date:  2003-12-20       Impact factor: 4.530

Review 8.  From genome sequence to integrated bioprocess for succinic acid production by Mannheimia succiniciproducens.

Authors:  Sang Yup Lee; Ji Mahn Kim; Hyohak Song; Jeong Wook Lee; Tae Yong Kim; Yu-Sin Jang
Journal:  Appl Microbiol Biotechnol       Date:  2008-03-14       Impact factor: 4.813

9.  Metabolic engineering of Escherichia coli for the production of L-valine based on transcriptome analysis and in silico gene knockout simulation.

Authors:  Jin Hwan Park; Kwang Ho Lee; Tae Yong Kim; Sang Yup Lee
Journal:  Proc Natl Acad Sci U S A       Date:  2007-04-26       Impact factor: 11.205

10.  Functional states of the genome-scale Escherichia coli transcriptional regulatory system.

Authors:  Erwin P Gianchandani; Andrew R Joyce; Bernhard Ø Palsson; Jason A Papin
Journal:  PLoS Comput Biol       Date:  2009-06-05       Impact factor: 4.475
  10 in total
  4 in total

1.  PATHLOGIC-S: a scalable Boolean framework for modelling cellular signalling.

Authors:  Liam G Fearnley; Lars K Nielsen
Journal:  PLoS One       Date:  2012-08-07       Impact factor: 3.240

2.  Knock-in/Knock-out (KIKO) vectors for rapid integration of large DNA sequences, including whole metabolic pathways, onto the Escherichia coli chromosome at well-characterised loci.

Authors:  Suriana Sabri; Jennifer A Steen; Mareike Bongers; Lars K Nielsen; Claudia E Vickers
Journal:  Microb Cell Fact       Date:  2013-06-24       Impact factor: 5.328

3.  A design-build-test cycle using modeling and experiments reveals interdependencies between upper glycolysis and xylose uptake in recombinant S. cerevisiae and improves predictive capabilities of large-scale kinetic models.

Authors:  Ljubisa Miskovic; Susanne Alff-Tuomala; Keng Cher Soh; Dorothee Barth; Laura Salusjärvi; Juha-Pekka Pitkänen; Laura Ruohonen; Merja Penttilä; Vassily Hatzimanikatis
Journal:  Biotechnol Biofuels       Date:  2017-06-26       Impact factor: 6.040

4.  In silico model-guided identification of transcriptional regulator targets for efficient strain design.

Authors:  Lokanand Koduru; Meiyappan Lakshmanan; Dong-Yup Lee
Journal:  Microb Cell Fact       Date:  2018-10-25       Impact factor: 5.328
  4 in total

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