Functional Genomics and NMR Spectroscopy

Powers, Robert

doi:10.2174/138620707782507331

Cited by 11 publications

(7 citation statements)

References 229 publications

(263 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…335 Magnetic resonance imaging (MRI), or in vivo chemical shift imaging (a spectroscopic variant of MRI) has long been used to follow a host of diseases in animal models and humans in vivo, and this is an expanding field in drug discovery. 336,337 This provides advantages in human physiology as in vivo studies are closer to the observed phenotype than animal or tissue models. It also circumvents the need for quenching metabolism, and indeed from in vivo spectroscopic studies of brain metabolism one can determine that the intracellular concentration of lactate is B1 mM, compared with the 410 mM concentration detected in tissue extracts as a result of post mortem metabolism of glucose and glycogen.…”

Section: (Vii) Spatial Mapping Of Metabolite Distributions In Tissues...mentioning

confidence: 99%

Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy

et al. 2011

View full text Add to dashboard Cite

The study of biological systems in a holistic manner (systems biology) is increasingly being viewed as a necessity to provide qualitative and quantitative descriptions of the emergent properties of the complete system. Systems biology performs studies focussed on the complex interactions of system components; emphasising the whole system rather than the individual parts. Many perturbations to mammalian systems (diet, disease, drugs) are multi-factorial and the study of small parts of the system is insufficient to understand the complete phenotypic changes induced. Metabolomics is one functional level tool being employed to investigate the complex interactions of metabolites with other metabolites (metabolism) but also the regulatory role metabolites provide through interaction with genes, transcripts and proteins (e.g. allosteric regulation). Technological developments are the driving force behind advances in scientific knowledge. Recent advances in the two analytical platforms of mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy have driven forward the discipline of metabolomics. In this critical review, an introduction to metabolites, metabolomes, metabolomics and the role of MS and NMR spectroscopy will be provided. The applications of metabolomics in mammalian systems biology for the study of the health-disease continuum, drug efficacy and toxicity and dietary effects on mammalian health will be reviewed. The current limitations and future goals of metabolomics in systems biology will also be discussed (374 references).

show abstract

Section: (Vii) Spatial Mapping Of Metabolite Distributions In Tissues...mentioning

confidence: 99%

Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy

et al. 2011

View full text Add to dashboard Cite

show abstract

“…Although the number of metabolites in a cell is usually one order lower compared with the number of genes or proteins, it is virtually impossible to simultaneously determine the complete metabolome with current technology. Mass spectrometry (MS) and nuclear magnetic resonance (NMR) are the most frequently used methods of detection in the analysis of the metabolome (Dunn, 2008;Powers, 2007). NMR is very useful in determining the structure of unknown compounds, but comes with the drawback of expensive instrumentation.…”

Section: The -Omes Of Systems Biologymentioning

confidence: 99%

Impact of yeast systems biology on industrial biotechnology

Petranović

Vemuri

2009

Journal of Biotechnology

View full text Add to dashboard Cite

“…To ensure that these analyses are accurate and unbiased, it is necessary to make as precise a prediction of the mass and retention time of a unknown metabolite as possible. This is essential to i ) the accuracy of compound recognition; ii ) the accurate calculation of chemical composition of a metabolite [9]; and iii ) the prediction of the function of unknown genes through metabolomics [8], [10], [11], [12], [13], [14].…”

Section: Introductionmentioning

confidence: 99%

An Ultra-Fast Metabolite Prediction Algorithm

Yang

Grant

2012

PLoS ONE

View full text Add to dashboard Cite

Small molecules are central to all biological processes and metabolomics becoming an increasingly important discovery tool. Robust, accurate and efficient experimental approaches are critical to supporting and validating predictions from post-genomic studies. To accurately predict metabolic changes and dynamics, experimental design requires multiple biological replicates and usually multiple treatments. Mass spectra from each run are processed and metabolite features are extracted. Because of machine resolution and variation in replicates, one metabolite may have different implementations (values) of retention time and mass in different spectra. A major impediment to effectively utilizing untargeted metabolomics data is ensuring accurate spectral alignment, enabling precise recognition of features (metabolites) across spectra. Existing alignment algorithms use either a global merge strategy or a local merge strategy. The former delivers an accurate alignment, but lacks efficiency. The latter is fast, but often inaccurate. Here we document a new algorithm employing a technique known as quicksort. The results on both simulated data and real data show that this algorithm provides a dramatic increase in alignment speed and also improves alignment accuracy.

show abstract

Functional Genomics and NMR Spectroscopy

Cited by 11 publications

References 229 publications

Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy

Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy

Impact of yeast systems biology on industrial biotechnology

An Ultra-Fast Metabolite Prediction Algorithm

Contact Info

Product

Resources

About