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MG-RAST version 4—lessons learned from a decade of low-budget ultra-high-throughput metagenome analysis
2017
Briefings in Bioinformatics
As technologies change, MG-RAST is adapting. Newly available software is being included to improve accuracy and performance. As a computational service constantly running large volume scientific workflows, MG-RAST is the right location to perform benchmarking and implement algorithmic or platform improvements, in many cases involving trade-offs between specificity, sensitivity and run-time cost. The work in [Glass EM, Dribinsky Y, Yilmaz P, et al. ISME J 2014;8:1-3] is an example; we use
doi:10.1093/bib/bbx105
pmid:29028869
fatcat:i72b4oguhnhkhisepyj27n6gia