%0 Journal Article %1 Witherden2017Using %A Witherden, Elizabeth A. %A Moyes, David L. %A Bruce, Kenneth D. %A Ehrlich, S. Dusko %A Shoaie, Saeed %D 2017 %J Current Opinion in Systems Biology %K flux-analysis host-pathogen microbiome %P 141--146 %R 10.1016/j.coisb.2017.05.003 %T Using systems biology approaches to elucidate cause and effect in host?microbiome interactions %U http://dx.doi.org/10.1016/j.coisb.2017.05.003 %V 3 %X Metagenomic gene catalogues to include archaea, fungi and bacteria proposed. System-level framework for processing multi-omics data sets developed. Review of Systems Biology approaches for studying host–microbiome interactions. The human microbiome is a diverse and complex ecosystem integral for healthy human development. Recent advances in next-generation sequencing technology have paved the way for a 'multi-omics' era of microbiome research, uncovering associations between microbial dysbiosis and disease. Our ability to harness the full potential of these 'multi-omics' datasets are currently constrained by several technical, analytical, computational and bioinformatics factors. However, it may be possible to overcome such limitations through the use of novel systems biology thinking and approaches, to integrate and analyse these large 'multi-omics' datasets. Thus, the question arises - can systems biology approaches pave the way to a new era in microbiome research; determining underlying mechanisms in health and disease, and identifying key microbial interactions and causalities?

@article{Witherden2017Using, abstract = { Metagenomic gene catalogues to include archaea, fungi and bacteria proposed. System-level framework for processing multi-omics data sets developed. Review of Systems Biology approaches for studying host–microbiome interactions. The human microbiome is a diverse and complex ecosystem integral for healthy human development. Recent advances in next-generation sequencing technology have paved the way for a 'multi-omics' era of microbiome research, uncovering associations between microbial dysbiosis and disease. Our ability to harness the full potential of these 'multi-omics' datasets are currently constrained by several technical, analytical, computational and bioinformatics factors. However, it may be possible to overcome such limitations through the use of novel systems biology thinking and approaches, to integrate and analyse these large 'multi-omics' datasets. Thus, the question arises - can systems biology approaches pave the way to a new era in microbiome research; determining underlying mechanisms in health and disease, and identifying key microbial interactions and causalities?}, added-at = {2018-12-02T16:09:07.000+0100}, author = {Witherden, Elizabeth A. and Moyes, David L. and Bruce, Kenneth D. and Ehrlich, S. Dusko and Shoaie, Saeed}, biburl = {https://www.bibsonomy.org/bibtex/22012cc0c7ae3778ede7ed9624e29803c/karthikraman}, citeulike-article-id = {14381055}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.coisb.2017.05.003}, doi = {10.1016/j.coisb.2017.05.003}, interhash = {616acab1f60e78f00e9d68470ae59192}, intrahash = {2012cc0c7ae3778ede7ed9624e29803c}, issn = {24523100}, journal = {Current Opinion in Systems Biology}, keywords = {flux-analysis host-pathogen microbiome}, month = jun, pages = {141--146}, posted-at = {2017-06-22 15:31:30}, priority = {2}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {Using systems biology approaches to elucidate cause and effect in host?microbiome interactions}, url = {http://dx.doi.org/10.1016/j.coisb.2017.05.003}, volume = 3, year = 2017 }