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ABSTRACT: The use of selective reaction monitoring (SRM) based LC-MS/MS analysis for the quantification of phosphorylation stoichiometry has been rapidly increasing. At the same time, the number of sites that can be monitored in a single LC-MS/MS experiment is also increasing. The manual processes associated with running these experiments have highlighted the need for computational assistance to quickly design MRM/SRM candidates.
PChopper has been developed to predict peptides that can be produced via enzymatic protein digest; this includes single enzyme digests, and combinations of enzymes. It also allows digests to be simulated in 'batch' mode and can combine information from these simulated digests to suggest the most appropriate enzyme(s) to use. PChopper also allows users to define the characteristic of their target peptides, and can automatically identify phosphorylation sites that may be of interest. Two application end points are available for interacting with the system; the first is a web based graphical tool, and the second is an API endpoint based on HTTP REST.
Service oriented architecture was used to rapidly develop a system that can consume and expose several services. A graphical tool was built to provide an easy to follow workflow that allows scientists to quickly and easily identify the enzymes required to produce multiple peptides in parallel via enzymatic digests in a high throughput manner.
BMC Bioinformatics 08/2011; 12:338. · 2.75 Impact Factor
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ABSTRACT: Biomarker identification, using network methods, depends on finding regular co-expression patterns; the overall connectivity is of greater importance than any single relationship. A second requirement is a simple algorithm for ranking patients on how relevant a gene-set is. For both of these requirements discretized data helps to first identify gene cliques, and then to stratify patients.We explore a biologically intuitive discretization technique which codes genes as up- or down-regulated, with values close to the mean set as unchanged; this allows a richer description of relationships between genes than can be achieved by positive and negative correlation. We find a close agreement between our results and the template gene-interactions used to build synthetic microarray-like data by SynTReN, which synthesizes "microarray" data using known relationships which are successfully identified by our method.We are able to split positive co-regulation into up-together and down-together and negative co-regulation is considered as directed up-down relationships. In some cases these exist in only one direction, with real data, but not with the synthetic data. We illustrate our approach using two studies on white blood cells and derived immortalized cell lines and compare the approach with standard correlation-based computations. No attempt is made to distinguish possible causal links as the search for biomarkers would be crippled by losing highly significant co-expression relationships. This contrasts with approaches like ARACNE and IRIS.The method is illustrated with an analysis of gene-expression for energy metabolism pathways. For each discovered relationship we are able to identify the samples on which this is based in the discretized sample-gene matrix, along with a simplified view of the patterns of gene expression; this helps to dissect the gene-sample relevant to a research topic--identifying sets of co-regulated and anti-regulated genes and the samples or patients in which this relationship occurs.
PLoS ONE 01/2011; 6(4):e18634. · 4.09 Impact Factor
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ABSTRACT: Several publications have described biological roles for human patatin-like phospholipases (PNPLAs) in the regulation of adipocyte differentiation. Here, we report on the characterization and expression profiling of 10 human PNPLAs. A variety of bioinformatics approaches were used to identify and characterize all PNPLAs encoded by the human genome. The genes described represent a divergent family, most with a highly conserved ortholog in several mammalian species. In silico characterization predicts that two of the genes function as integral membrane proteins and are regulated by cAMP/cGMP. A structurally guided protein alignment of the patatin-like domain identifies a number of conserved residues in all family members. Quantitative PCR was used to determine the expression profile of each family member. Affymetrix-based profiling of a human preadipocyte cell line identified several members that are differentially regulated during cell differentiation. Cumulative data suggest that patatin-like genes normally expressed at very low levels are induced in response to environmental signals. Given the observed conservation of the patatin fold and lipase motif in all human PNPLAs, a single nomenclature to describe the PNPLA family is proposed.
The Journal of Lipid Research 10/2006; 47(9):1940-9. · 5.56 Impact Factor
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Daniel J Crowther
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ABSTRACT: Microarrays provide the ability to measure the expression of thousands of genes in parallel. From target discovery through to uses in the clinic, microarrays are having an enormous impact on research in the pharmaceutical industry. In particular, microarrays have applications in genome annotation, they contribute to improving our disease understanding and can be used in the drug development pipeline to improve selection of biological targets and lead compounds.
Current Opinion in Pharmacology 11/2002; 2(5):551-4. · 6.86 Impact Factor
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ABSTRACT: For almost two decades, 1H-NMR spectroscopy has been used as an 'open' system to study the temporal changes in the biochemical composition of biofluids, including urine, in response to adverse toxic events. Many of these in vivo studies have reported changes in individual metabolites and patterns of metabolites that correlated with toxicological changes. However, many of the proposed novel biomarkers are common to a number of different types of toxicity. These may therefore reflect non-specific effects of toxicity, such as weight loss, rather than a specific pathology. A study was carried out to investigate the non-specific effects on urinary metabolite profiles by administering four hepatotoxic compounds, as a single dose, to rats at two dose levels: hydrazine hydrate (0.06 or 0.08 g kg (1)), 1,2-dimethylhydrazine (0.1 or 0.3 g kg (-1)), alpha-napthylisothiocyanate (0.1 or 0.15 g kg(-1)) and carbon tetrachloride (1.58 or 3.16 g kg(-1)). The study included weight-matched control animals along with those that were dosed, which were then 'pair-fed' with the treated animals so they achieved a similar weight loss. The urinary metabolite profiles were investigated over time using 1H-NMR spectroscopy and compared with the pathology from the same animals. The temporal changes were analysed statistically using multivariate statistical data analysis including principal component analysis, partial least squares, parallel factor analysis and Fisher's criteria. A number of metabolites associated with energy metabolism or which are partially dietary in origin, such as creatine, creatinine, tricarboxylic acid (TCA) cycle intermediates, phenylacetylglycine, fumarate, glucose, taurine, fatty acids and N-methylnicotinamide, showed altered levels in the urine of treated and pair-fed animals. Many of these changes correlated well with weight loss. Interestingly, there was no increase in ketone bodies (acetate and beta-hydroxybutyrate), which might be expected if energy metabolism was switched from glycolysis to fatty acid beta-oxidation. In some instances, the metabolites that changed were considered to be non-specific markers of toxicity, but were also identified as markers of a specific type of toxicity. For example, taurine was raised significantly in carbon tetrachloride-treated animals but reduced in the pair-fed group. However, raised urinary bile acid levels were only seen after alpha-napthylisothiocyanate treatment. The methodology, statistical analysis used and the data generated will help improve the identification of specific markers or patterns of urinary markers of specific toxic effects.
Biomarkers 9(2):156-79. · 2.21 Impact Factor
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ABSTRACT: Proton nuclear magnetic resonance (1H NMR) spectroscopic analysis of mixtures has been used extensively for a variety of applications ranging from the analysis of plant extracts, wine, and food to the evaluation of toxicity in animals. For example, NMR analysis of urine samples has been used extensively for biomarker discovery and, more simply, for the construction of classification models of toxicity, disease, and biochemical phenotype. However, NMR spectra of complex mixtures typically show unwanted local peak shifts caused by matrix and instrument variability, which must be compensated for prior to statistical analysis and interpretation of the data. One approach is to align the spectral peaks across the data set. An efficient and fast warping algorithm is required as the signals typically contain ca. 32,000-64,000 data points and there can be several thousand spectra in a data set. As demonstrated in our study, the iterative fuzzy warping algorithm fulfills these requirements and can be used on-line for an alignment of the NMR spectra. Correlation coefficients between the aligned and target spectra are used as the evaluation function for the algorithm, and its performance is compared with those of other published warping methods.
Journal of Chemical Information and Modeling 46(2):863-75. · 4.68 Impact Factor
