Literature DB >> 15256207

Mapping phenotypic landscapes using DNA micro-arrays.

Michael D Lynch1, Ryan T Gill, Gregory Stephanopoulos.   

Abstract

Inverse metabolic engineering is a useful approach for engineering phenotypes in biological systems. The overarching objective of this approach is to combine the power of evolutionary engineering approaches with the precision of constructive metabolic engineering strategies. Often the difficulty in this approach is elucidating the genetic basis of the phenotypes that emerge as a result of evolutionary mechanisms. As a result of advances in genomics technologies, several techniques now exist that substantially improve researchers ability to identify such genes. Metabolic engineers now have the ability to map phenotypic landscapes of considerable genetic diversity, which should improve understanding of the relationships that exist among phenotype, genotype, and environment. In this mini-review, we will discuss several of such genomics tools that may be useful in developing inverse metabolic engineering strategies and, in particular, mapping phenotypic landscapes.

Mesh:

Year:  2004        PMID: 15256207     DOI: 10.1016/j.ymben.2004.01.002

Source DB:  PubMed          Journal:  Metab Eng        ISSN: 1096-7176            Impact factor:   9.783


  4 in total

Review 1.  Rapid prototyping of microbial cell factories via genome-scale engineering.

Authors:  Tong Si; Han Xiao; Huimin Zhao
Journal:  Biotechnol Adv       Date:  2014-11-20       Impact factor: 14.227

2.  A comparison of alternative 60-mer probe designs in an in-situ synthesized oligonucleotide microarray.

Authors:  Danielle L Leiske; Anis Karimpour-Fard; Patrick S Hume; Benjamin D Fairbanks; Ryan T Gill
Journal:  BMC Genomics       Date:  2006-04-04       Impact factor: 3.969

Review 3.  Strategies for the multiplex mapping of genes to traits.

Authors:  Andrew Garst; Michael Lynch; Ron Evans; Ryan T Gill
Journal:  Microb Cell Fact       Date:  2013-10-30       Impact factor: 5.328

4.  Genome-wide identification of genes conferring energy related resistance to a synthetic antimicrobial peptide (Bac8c).

Authors:  Eileen C Spindler; Nanette R Boyle; Robert E W Hancock; Ryan T Gill
Journal:  PLoS One       Date:  2013-01-31       Impact factor: 3.240

  4 in total

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