Publications
42 results found
Pinney JW, Amoutzias GD, Rattray M, et al., 2007, Reconstruction of ancestral protein interaction networks for the bZIP transcription factors., Proc Natl Acad Sci U S A, Vol: 104, Pages: 20449-20453
As whole-genome protein-protein interaction datasets become available for a wide range of species, evolutionary biologists have the opportunity to address some of the unanswered questions surrounding the evolution of these complex systems. Protein interaction networks from divergent organisms may be compared to investigate how gene duplication, deletion, and rewiring processes have shaped the evolution of their contemporary structures. However, current approaches for comparing observed networks from multiple species lack the phylogenetic context necessary to reconstruct the evolutionary history of a network. Here we show how probabilistic modeling can provide a platform for the quantitative analysis of multiple protein interaction networks. We apply this technique to the reconstruction of ancestral networks for the bZIP family of transcription factors and find that excellent agreement is obtained with an alternative sequence-based method for the prediction of leucine zipper interactions. Further analysis shows our probabilistic method to be significantly more robust to the presence of noise in the observed network data than a simple parsimony-based approach. In addition, the integration of evidence over multiple species means that the same method may be used to improve the quality of noisy interaction data for extant species. The ancestral states of a protein interaction network have been reconstructed here by using an explicit probabilistic model of network evolution. We anticipate that this model will form the basis of more general methods for probing the evolutionary history of biochemical networks.
Pinney JW, Papp B, Hyland C, et al., 2007, Metabolic reconstruction and analysis for parasite genomes., Trends Parasitol, Vol: 23, Pages: 548-554
With the completion of sequencing projects for several parasite genomes, efforts are ongoing to make sense of this mass of information in terms of the gene products encoded and their interactions in the growth, development and survival of parasites. The emerging science of systems biology aims to explain the complex relationship between genotype and phenotype by using network models. One area in which this approach has been particularly successful is in the modeling of metabolism. With an accurate picture of the set of metabolic reactions encoded in a genome, it is now possible to identify enzymes or transporters that might be viable targets for new drugs. Because these predictions greatly depend on the quality and completeness of the genome annotation, there are substantial efforts in the scientific community to increase the numbers of metabolic enzymes identified. In this review, we discuss the opportunities for using metabolic reconstruction and analysis tools in parasitology research, and their applications to protozoan parasites.
Holden BJ, Pinney JW, Lovell SC, et al., 2007, An exploration of alternative visualisations of the basic helix-loop-helix protein interaction network., BMC Bioinformatics, Vol: 8
BACKGROUND: Alternative representations of biochemical networks emphasise different aspects of the data and contribute to the understanding of complex biological systems. In this study we present a variety of automated methods for visualisation of a protein-protein interaction network, using the basic helix-loop-helix (bHLH) family of transcription factors as an example. RESULTS: Network representations that arrange nodes (proteins) according to either continuous or discrete information are investigated, revealing the existence of protein sub-families and the retention of interactions following gene duplication events. Methods of network visualisation in conjunction with a phylogenetic tree are presented, highlighting the evolutionary relationships between proteins, and clarifying the context of network hubs and interaction clusters. Finally, an optimisation technique is used to create a three-dimensional layout of the phylogenetic tree upon which the protein-protein interactions may be projected. CONCLUSION: We show that by incorporating secondary genomic, functional or phylogenetic information into network visualisation, it is possible to move beyond simple layout algorithms based on network topology towards more biologically meaningful representations. These new visualisations can give structure to complex networks and will greatly help in interpreting their evolutionary origins and functional implications. Three open source software packages (InterView, TVi and OptiMage) implementing our methods are available.
Hakes L, Pinney JW, Lovell SC, et al., 2007, All duplicates are not equal: the difference between small-scale and genome duplication., Genome Biol, Vol: 8
BACKGROUND: Genes in populations are in constant flux, being gained through duplication and occasionally retained or, more frequently, lost from the genome. In this study we compare pairs of identifiable gene duplicates generated by small-scale (predominantly single-gene) duplications with those created by a large-scale gene duplication event (whole-genome duplication) in the yeast Saccharomyces cerevisiae. RESULTS: We find a number of quantifiable differences between these data sets. Whole-genome duplicates tend to exhibit less profound phenotypic effects when deleted, are functionally less divergent, and are associated with a different set of functions than their small-scale duplicate counterparts. At first sight, either of these latter two features could provide a plausible mechanism by which the difference in dispensability might arise. However, we uncover no evidence suggesting that this is the case. We find that the difference in dispensability observed between the two duplicate types is limited to gene products found within protein complexes, and probably results from differences in the relative strength of the evolutionary pressures present following each type of duplication event. CONCLUSION: Genes, and the proteins they specify, originating from small-scale and whole-genome duplication events differ in quantifiable ways. We infer that this is not due to their association with different functional categories; rather, it is a direct result of biases in gene retention.
Hyland C, Pinney JW, McConkey GA, et al., 2006, metaSHARK: a WWW platform for interactive exploration of metabolic networks., Nucleic Acids Res, Vol: 34, Pages: W725-W728
The metaSHARK (metabolic search and reconstruction kit) web server offers users an intuitive, fully interactive way to explore the KEGG metabolic network via a WWW browser. Metabolic reconstruction information for specific organisms, produced by our automated SHARKhunt tool or from other programs or genome annotations, may be uploaded to the website and overlaid on the generic network. Additional data from gene expression experiments can also be incorporated, allowing the visualization of differential gene expression in the context of the predicted metabolic network. metaSHARK is available at http://bioinformatics.leeds.ac.uk/shark/.
Manfield IW, Jen CH, Pinney JW, et al., 2006, Arabidopsis Co-expression Tool (ACT): web server tools for microarray-based gene expression analysis., Nucleic Acids Res, Vol: 34, Pages: W504-W509
The Arabidopsis Co-expression Tool, ACT, ranks the genes across a large microarray dataset according to how closely their expression follows the expression of a query gene. A database stores pre-calculated co-expression results for approximately 21,800 genes based on data from over 300 arrays. These results can be corroborated by calculation of co-expression results for user-defined sub-sets of arrays or experiments from the NASC/GARNet array dataset. Clique Finder (CF) identifies groups of genes which are consistently co-expressed with each other across a user-defined co-expression list. The parameters can be altered easily to adjust cluster size and the output examined for optimal inclusion of genes with known biological roles. Alternatively, a Scatter Plot tool displays the correlation coefficients for all genes against two user-selected queries on a scatter plot which can be useful for visual identification of clusters of genes with similar r-values. User-input groups of genes can be highlighted on the scatter plots. Inclusion of genes with known biology in sets of genes identified using CF and Scatter Plot tools allows inferences to be made about the roles of the other genes in the set and both tools can therefore be used to generate short lists of genes for further characterization. ACT is freely available at www.Arabidopsis.leeds.ac.uk/ACT.
Jen CH, Manfield IW, Michalopoulos I, et al., 2006, The Arabidopsis co-expression tool (ACT): a WWW-based tool and database for microarray-based gene expression analysis., Plant J, Vol: 46, Pages: 336-348
We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (ACT), based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression patterns are correlated across selected experiments or the complete data set. Results are accompanied by estimates of the statistical significance of the correlation relationships, expressed as probability (P) and expectation (E) values. Additionally, highly ranked genes on a correlation list can be examined using the novel clique finder tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots, and dissection into cliques of co-regulated genes. We illustrate the applications of the software by analysing genes encoding functionally related proteins, as well as pathways involved in plant responses to environmental stimuli. These analyses demonstrate novel biological relationships underlying the observed gene co-expression patterns. To demonstrate the ability of the software to develop testable hypotheses on gene function within a defined biological process we have used the example of cell wall biosynthesis genes. The resource is freely available at http://www.arabidopsis.leeds.ac.uk/ACT/
Taib M, Pinney JW, Westhead DR, et al., 2005, Differential expression and extent of fungal/plant and fungal/bacterial chitinases of Aspergillus fumigatus., Arch Microbiol, Vol: 184, Pages: 78-81
We provide the first indication of the extent of the complex chitinolytic system of a filamentous fungus. Phylogenetic analysis of the 14 apparent chitinases of the opportunistic fungal pathogen Aspergillus fumigatus identified four and ten enzymes related to plant and bacterial chitinases, respectively. Further, real time-RT-PCR studies revealed distinct patterns of gene expression, consistent with morphogenetic or nutritional roles, for members of the fungal/plant or fungal/bacterial sub-families, respectively. Our results provide a basis for future studies with A. fumigatus chitinases, which may lead to the exploitation of these enzymes, or their regulators, in the development of novel drug strategies.
Pinney JW, Shirley MW, McConkey GA, et al., 2005, metaSHARK:: software for automated metabolic network prediction from DNA sequence and its application to the genomes of <i>Plasmodium falciparum</i> and <i>Eimeria tenella</i>, NUCLEIC ACIDS RESEARCH, Vol: 33, Pages: 1399-1409, ISSN: 0305-1048
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McConkey GA, Pinney JW, Westhead DR, et al., 2004, Annotating the Plasmodium genome and the enigma of the shikimate pathway., Trends Parasitol, Vol: 20, Pages: 60-65, ISSN: 1471-4922
The completion of the Plasmodium falciparum genome sequence heralds a new era in the effort to identify all the parasite's genes along with their cellular functions. A combination of bioinformatics and experimental proof will facilitate this process. Many enzymes in metabolic processes have been identified, but several examples exist of incomplete pathways, such as the shikimate pathway. This review uses the example of the shikimate pathway to examine the application of bioinformatics to lead experimental design in post-genomic biology.
Pinney JW, Westhead DR, McConkey GA, 2003, Petri Net representations in systems biology., Biochem Soc Trans, Vol: 31, Pages: 1513-1515, ISSN: 0300-5127
The mathematical structures known as Petri Nets have recently become the focus of much research effort in both the structural and quantitative analysis of all kinds of biological networks. This review provides a very brief summary of these interesting new research directions.
Pinney J, Yasuda O, 2001, Correlations of errors in measurements of CP violation at neutrino factories, Phys. Rev. D, Vol: 64
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