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dc.contributor.authorAlam, Intikhab
dc.date.accessioned2016-03-16T12:53:28Z
dc.date.available2016-03-16T12:53:28Z
dc.date.issued2016-01-26
dc.identifier.urihttp://hdl.handle.net/10754/601405
dc.description.abstractMore and more genomes and metagenomes are being sequenced since the advent of Next Generation Sequencing Technologies (NGS). Many metagenomic samples are collected from a variety of environments, each exhibiting a different environmental profile, e.g. temperature, environmental chemistry, etc… These metagenomes can be profiled to unearth enzymes relevant to several industries based on specific enzyme properties such as ability to work on extreme conditions, such as extreme temperatures, salinity, anaerobically, etc.. In this work, we present the DMAP platform comprising of a high-throughput metagenomic annotation pipeline and a data-warehouse for comparisons and profiling across large number of metagenomes. We developed two reference databases for profiling of important genes, one containing enzymes related to different industries and the other containing genes with potential bioactivity roles. In this presentation we describe an example analysis of a large number of publicly available metagenomic sample from TARA oceans study (Science 2015) that covers significant part of world oceans.
dc.titleHigh throughtput comparisons and profiling of metagenomes for industrially relevant enzymes
dc.typePresentation
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.conference.dateJanuary 25-27, 2016
dc.conference.nameKAUST Research Conference on Computational and Experimental Interfaces of Big Data and Biotechnology
dc.conference.locationKAUST, Thuwal, Saudi Arabia
kaust.personAlam, Intikhab


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