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
Gene expression profiling of hormonal regulation related to the residual feed intake of Holstein cattle
An accumulation of over a decade of research in cattle has shown that genetic selection for decreased residual feed intake (RFI), defined as the difference between an animal's actual feed intake and its expected feed intake, is a viable option for improving feed efficiency and reducing the feed requirements of herds, thereby improving the profitability of cattle producers. Hormonal regulation is one of the most important factors in feed intake. To determine the relationship between hormones and feed efficiency, we performed gene expression profiling of jugular vein serum on hormonal regulation of Chinese Holstein cattle with low and high RFI coefficients. 857 differential expression genes (from 24683 genes) were found. Among these, 415 genes were up-regulated and 442 genes were down-regulated in the low RFI group. The gene ontology (GO) search revealed 6 significant terms and 64 genes associated with hormonal regulation, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) selected the adipocytokine signaling pathway, insulin signaling pathway. In conclusion, the study indicated that the molecular expression of genes associated with hormonal regulation differs in dairy cows, depending on their RFI coefficients, and that these differences may be related to the molecular regulation of the leptin-NPY and insulin signaling pathways. (C) 2015 Elsevier Inc. All rights reserved.
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