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
The influenza A virus infects a broad range of species and spreads easily through the respiratory tract. Because of these characteristics, the influenza A virus has caused pandemic disease in humans and livestock. To investigate the early molecular responses after influenza A virus infection in chickens, we infected tracheal epithelial cells derived from 20-day-old chick embryos with influenza A virus (H1N1). The gene expression patterns of the infected tracheal epithelial cells were analyzed via DNA microarray at different time points (0, 6, 12, 24, and 36 hr) after viral infection. Differentially expressed genes were identified at 6, 12, 24, and 36 hours post infection. A total of 1,936, 2,168, 3,670 and 2,894 genes were upregulated (>= 2-fold, P < 0.05), whereas 884, 592, 1,503 and 1,925 genes were downregulated at the respective time points (<= 0.5-fold, P < 0.05). When the differentially expressed genes were functionally categorized, immune-related and defense response gene ontology terms were detected in 12, 24, or 36 hours post infection. Interestingly, in the defense response, most of the gallinacin (GAL) genes were rapidly induced within 24 hr post infection. Subsequently, we predicted transcription factor binding sites within promoters of the GAL gene family, and analyzed the gene expression pattern for the common GAL gene regulatory factors to identify the viral infection-induced immune mechanism. Our results might contribute to an understanding of early host responses and regulatory mechanisms for host defense peptide induction against viral infections in chicken.
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