Literature DB >> 16615085

A bioinformatician's view of the metabolome.

Irene Nobeli1, Janet M Thornton.   

Abstract

The study of a collection of metabolites as a whole (metabolome), as opposed to isolated small molecules, is a fast-growing field promising to take us one step further towards understanding cell biology, and relating the genetic capabilities of an organism to its observed phenotype. The new sciences of metabolomics and metabonomics can exploit a variety of existing experimental and computational methods, but they also require new technology that can deal with both the amount and the diversity of the data relating to the rich world of metabolites. More specifically, the collaboration between bioinformaticians and chemoinformaticians promises to advance our view of cognate molecules, by shedding light on their atomic structure and properties. Modelling of the interactions of metabolites with other entities in the cell, and eventually complete modelling of reaction pathways will be essential for analysis of the experimental data, and prediction of an organism's response to environmental challenges. 2006 Wiley Periodicals, Inc.

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Year:  2006        PMID: 16615085     DOI: 10.1002/bies.20414

Source DB:  PubMed          Journal:  Bioessays        ISSN: 0265-9247            Impact factor:   4.345


  28 in total

1.  LVIS553 transcriptional regulator specifically recognizes novobiocin as an effector molecule.

Authors:  Fernando A Pagliai; Christopher L Gardner; Santosh G Pande; Graciela L Lorca
Journal:  J Biol Chem       Date:  2010-03-22       Impact factor: 5.157

2.  Metabolomics in premature labor: a novel approach to identify patients at risk for preterm delivery.

Authors:  Roberto Romero; Shali Mazaki-Tovi; Edi Vaisbuch; Juan Pedro Kusanovic; Tinnakorn Chaiworapongsa; Ricardo Gomez; Jyh Kae Nien; Bo Hyun Yoon; Moshe Mazor; Jingqin Luo; David Banks; John Ryals; Chris Beecher
Journal:  J Matern Fetal Neonatal Med       Date:  2010-05-26

Review 3.  The use of high-dimensional biology (genomics, transcriptomics, proteomics, and metabolomics) to understand the preterm parturition syndrome.

Authors:  R Romero; J Espinoza; F Gotsch; J P Kusanovic; L A Friel; O Erez; S Mazaki-Tovi; N G Than; S Hassan; G Tromp
Journal:  BJOG       Date:  2006-12       Impact factor: 6.531

Review 4.  Database resources in metabolomics: an overview.

Authors:  Eden P Go
Journal:  J Neuroimmune Pharmacol       Date:  2009-05-07       Impact factor: 4.147

5.  apLCMS--adaptive processing of high-resolution LC/MS data.

Authors:  Tianwei Yu; Youngja Park; Jennifer M Johnson; Dean P Jones
Journal:  Bioinformatics       Date:  2009-05-04       Impact factor: 6.937

6.  Biomarker discovery in animal health and disease: the application of post-genomic technologies.

Authors:  Rowan E Moore; Jennifer Kirwan; Mary K Doherty; Phillip D Whitfield
Journal:  Biomark Insights       Date:  2007-07-10

7.  Quantitative global studies of reactomes and metabolomes using a vectorial representation of reactions and chemical compounds.

Authors:  Juan C Triviño; Florencio Pazos
Journal:  BMC Syst Biol       Date:  2010-04-20

8.  Organization of GC/MS and LC/MS metabolomics data into chemical libraries.

Authors:  Corey D Dehaven; Anne M Evans; Hongping Dai; Kay A Lawton
Journal:  J Cheminform       Date:  2010-10-18       Impact factor: 5.514

9.  Identification of biochemical differences between different forms of male infertility by nuclear magnetic resonance (NMR) spectroscopy.

Authors:  Varshini Jayaraman; Soumita Ghosh; Arjun Sengupta; Sudha Srivastava; H M Sonawat; Pratap Kumar Narayan
Journal:  J Assist Reprod Genet       Date:  2014-06-26       Impact factor: 3.412

10.  E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs.

Authors:  Yoshihiro Yamanishi; Masahiro Hattori; Masaaki Kotera; Susumu Goto; Minoru Kanehisa
Journal:  Bioinformatics       Date:  2009-06-15       Impact factor: 6.937

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