The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
Generation, analysis and functional annotation of expressed sequence tags from the ectoparasitic mite Psoroptes ovis
Background: Sheep scab is caused by Psoroptes ovis and is arguably the most important ectoparasitic disease affecting sheep in the UK. The disease is highly contagious and causes and considerable pruritis and irritation and is therefore a major welfare concern. Current methods of treatment are unsustainable and in order to elucidate novel methods of disease control a more comprehensive understanding of the parasite is required. To date, no full genomic DNA sequence or large scale transcript datasets are available and prior to this study only 484 P. ovis expressed sequence tags (ESTs) were accessible in public databases. Results: In order to further expand upon the transcriptomic coverage of P. ovis thus facilitating novel insights into the mite biology we undertook a larger scale EST approach, incorporating newly generated and previously described P. ovis transcript data and representing the largest collection of P. ovis ESTs to date. We sequenced 1,574 ESTs and assembled these along with 484 previously generated P. ovis ESTs, which resulted in the identification of 1,545 unique P. ovis sequences. BLASTX searches identified 961 ESTs with significant hits (E-value < 1E-04) and 584 novel P. ovis ESTs. Gene Ontology (GO) analysis allowed the functional annotation of 880 ESTs and included predictions of signal peptide and transmembrane domains; allowing the identification of potential P. ovis excreted/secreted factors, and mapping of metabolic pathways. Conclusions: This dataset currently represents the largest collection of P. ovis ESTs, all of which are publicly available in the GenBank EST database (dbEST) (accession numbers FR748230 - FR749648). Functional analysis of this dataset identified important homologues, including house dust mite allergens and tick salivary factors. These findings offer new insights into the underlying biology of P. ovis, facilitating further investigations into mite biology and the identification of novel methods of intervention.
Inappropriate format for Document type, expected simple value but got array, please use list format