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A metagenomics analysis of rumen microbiome

Walsh, Paul, Palu, Cintia, Kelly, Brian, Lawor, Brendan, Wassan, Jyotsna Talreja, Zheng, Huiru and Wang, Haiying / HY (2017) A metagenomics analysis of rumen microbiome. In: 2017 IEEE International Conference on Bioinformatics and Biomedicine, Kansas City, MO, USA. IEEE. 6 pp. [Conference contribution]

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URL: http://dx.doi.org/10.1109/BIBM.2017.8217980

DOI: 10.1109/BIBM.2017.8217980

Abstract

Climate change and food security are significant global challenges facing society. The dairy industry is inextricably linked to these challenges as it is concerned with the economies of food production, while acknowledging that it is a major contributor to greenhouse gas production. Action by microbial communities in the rumen is responsible for efficient breakdown of plant matter for food conversion, but a by-product of this action is substantial methane production. Insight into food conversion and methane production in rumen microbiota is possible through metagenomics analysis, which is the analysis of microbial communities and their interactions with the environment. However, metagenomic analysis is hampered by the sheer volume and complexity of data that needs to be processed. This paper presents a bioinformatics pipeline and visualisation platform that facilitates deep analysis of microbial communities, under various conditions in cattle rumen, with the aim of leading to significant impact on probiotic supplement usage, methane production and feed conversion efficiency. This pipeline was developed as part of the EU H2020 MetaPlat project and will pave the way for a more optimal usage of metagenomic datasets, thus reducing the number of animals necessary to be engaged in such studies. This will ensure better and more economic animal welfare, better use of resources and lessen the impact of the dairy industry on climate change.

Item Type:Conference contribution (Paper)
Keywords:Metagenomics; cattle rumen; visualisation; classification, cloud architecture
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute > Smart Environments
Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:39631
Deposited By: Dr Huiru Zheng
Deposited On:23 Apr 2018 14:55
Last Modified:23 Apr 2018 14:55

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