DataBiNS: A BioMoby-based data-mining workflow for biological pathways and non-synonymous SNPs. Song, Y., Kawas, E., Good, B., Wilkinson, M., & Tebbutt, S. Bioinformatics, 2007.
doi  abstract   bibtex   
Summary: DataBiNS is a custom-designed BioMoby Web Service workflow that integrates non-synonymous coding single nucleotide polymorphisms (nsSNPs) data with structure/function and pathway data for the relevant protein. A KEGG Pathway Identifier representing a specific human biological pathway initializes the DataBiNS workflow. The workflow retrieves a list of publications, gene ontology annotations and nsSNP information for each gene involved in the biological pathway. Manual inspection of output data from several trial runs confirms that all expected information is appropriately retrieved by the workflow services. The use of an automated BioMoby workflow, rather than manual 'surfing', to retrieve the necessary data, significantly reduces the effort required for functional interpretation of SNP data, and thus encourages more speculative investigation. Moreover, the modular nature of the individual BioMoby Services enables fine-grained reusing of each service in other workflows, thus reducing the effort required to achieve similar investigations in the future. © 2007 Oxford University Press.
@article{
 title = {DataBiNS: A BioMoby-based data-mining workflow for biological pathways and non-synonymous SNPs},
 type = {article},
 year = {2007},
 volume = {23},
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 abstract = {Summary: DataBiNS is a custom-designed BioMoby Web Service workflow that integrates non-synonymous coding single nucleotide polymorphisms (nsSNPs) data with structure/function and pathway data for the relevant protein. A KEGG Pathway Identifier representing a specific human biological pathway initializes the DataBiNS workflow. The workflow retrieves a list of publications, gene ontology annotations and nsSNP information for each gene involved in the biological pathway. Manual inspection of output data from several trial runs confirms that all expected information is appropriately retrieved by the workflow services. The use of an automated BioMoby workflow, rather than manual 'surfing', to retrieve the necessary data, significantly reduces the effort required for functional interpretation of SNP data, and thus encourages more speculative investigation. Moreover, the modular nature of the individual BioMoby Services enables fine-grained reusing of each service in other workflows, thus reducing the effort required to achieve similar investigations in the future. © 2007 Oxford University Press.},
 bibtype = {article},
 author = {Song, Y.C. and Kawas, E. and Good, B.M. and Wilkinson, M.D. and Tebbutt, S.J.},
 doi = {10.1093/bioinformatics/btl648},
 journal = {Bioinformatics},
 number = {6}
}

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