Getting the most out of parasitic helminth transcriptomes using HelmDB: implications for biology and biotechnology.

摘要: Compounded by a massive global food shortage, many parasitic diseases have devastating, long-term impact on animal and human health welfare worldwide. Parasitic helminths (worms) affect the of billions animals. Unlocking systems biology these neglected pathogens will underpin design new improved interventions against them. Currently, functional annotation genomic transcriptomic sequence data for socio-economically important worms relies almost exclusively comparative bioinformatic analyses using model organism- other databases. However, genes gene products (often > 50%) cannot be annotated this approach, because they are specific to parasites and/or do not identifiable homologs in organisms which available. This inability fully annotate transcriptomes predicted proteomes is major challenge constrains our understanding parasites, interactions with their hosts parasitism pathogenesis disease molecular level. In present article, we compiled sets key, socioeconomically helminths, constructed validated curated database, called HelmDB (www.helmdb.org). We demonstrate how database can used effectively improvement employing integration clustering. Importantly, provides practical user-friendly toolkit browsing among divergent helminth groups (including nematodes trematodes), should readily adaptable applicable wide range organisms. web-based, integrative assist ‘systems biology’ studies discovery prioritization novel drug vaccine targets. focus pathway toward developing approaches treatment control diseases, potential biotechnological outcomes.