Literature DB >> 11485321

Automated mode-of-action detection by metabolic profiling.

N Aranìbar1, B K Singh, G W Stockton, K H Ott.   

Abstract

Rapid classification and identification of the mode-of-action of bioactive compounds applied to plants can be achieved by a robust and easy-to-use metabolic-profiling method. This method uses artificial neural network analysis of one-dimensional proton NMR spectra of aqueous plant extracts to rapidly classify changes in the total metabolic profile caused by application of crop protection chemicals. Copyright 2001 Academic Press.

Mesh：

Year:  2001        PMID： 11485321     DOI： 10.1006/bbrc.2001.5350

Source DB:  PubMed          Journal:  Biochem Biophys Res Commun        ISSN： 0006-291X            Impact factor:   3.575


  7 in total

1.  Metabolomics and machine learning: explanatory analysis of complex metabolome data using genetic programming to produce simple, robust rules.

Authors:  Douglas B Kell
Journal:  Mol Biol Rep       Date:  2002       Impact factor: 2.316

2.  Clarification of pathway-specific inhibition by Fourier transform ion cyclotron resonance/mass spectrometry-based metabolic phenotyping studies.

Authors:  Akira Oikawa; Yukiko Nakamura; Tomonori Ogura; Atsuko Kimura; Hideyuki Suzuki; Nozomu Sakurai; Yoko Shinbo; Daisuke Shibata; Shigehiko Kanaya; Daisaku Ohta
Journal:  Plant Physiol       Date:  2006-08-11       Impact factor: 8.340

3.  Discrimination of modes of action of antifungal substances by use of metabolic footprinting.

Authors:  Jess Allen; Hazel M Davey; David Broadhurst; Jem J Rowland; Stephen G Oliver; Douglas B Kell
Journal:  Appl Environ Microbiol       Date:  2004-10       Impact factor: 4.792

4.  Temporally resolved GC-MS-based metabolic profiling of herbicide treated plants treated reveals that changes in polar primary metabolites alone can distinguish herbicides of differing mode of action.

Authors:  Sandra Trenkamp; Peter Eckes; Marco Busch; Alisdair R Fernie
Journal:  Metabolomics       Date:  2008-12-13       Impact factor: 4.290

5.  A composite transcriptional signature differentiates responses towards closely related herbicides in Arabidopsis thaliana and Brassica napus.

Authors:  Malay Das; Jay R Reichman; Georg Haberer; Gerhard Welzl; Felipe F Aceituno; Michael T Mader; Lidia S Watrud; Thomas G Pfleeger; Rodrigo A Gutiérrez; Anton R Schäffner; David M Olszyk
Journal:  Plant Mol Biol       Date:  2009-12-31       Impact factor: 4.076

Review 6.  Omics methods for probing the mode of action of natural and synthetic phytotoxins.

Authors:  Stephen O Duke; Joanna Bajsa; Zhiqiang Pan
Journal:  J Chem Ecol       Date:  2013-01-27       Impact factor: 2.626

7.  Untargeted metabolomics reveals a lack of synergy between nifurtimox and eflornithine against Trypanosoma brucei.

Authors:  Isabel M Vincent; Darren J Creek; Karl Burgess; Debra J Woods; Richard J S Burchmore; Michael P Barrett
Journal:  PLoS Negl Trop Dis       Date:  2012-05-01
  7 in total

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