A compilation excretory secretory proteins from parasitic helminths. Helminth Secretome Database serves as a repository for ES proteins predicted using classical and non-classical secretory pathways, from EST data for 78 helminth species (64 nematodes, 7 trematodes and 7 cestodes) ranging from parasitic to free-living organisms. This approach can be used on new large-scale transcriptomic data sets from NGS platforms, for rapid prediction and annotation of ES proteins.
Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney, NSW, Australia; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
HSD funding source(s)
This study was supported by Macquarie University with the grant of Australian Postgraduate Award scholarship and Post Graduate Research Fund.