dc.date.accessioned | 2020-10-29T14:15:36Z | |
dc.date.available | 2020-10-29T14:15:36Z | |
dc.date.issued | 2016-09-09 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/128236 | |
dc.description.abstract | Prochlorococcus is the smallest and most abundant photosynthetic organism on earth. Despite its tiny size, it’s an organism of global importance. In recent decades, researchers have sequenced the organisms’ genomes. Advances in sequencing technologies have generated massive databases of ocean genomic data from around the world. So while there is rich data available about Prochlorococcus, mining the value of this Big Data is difficult because it requires simultaneously analyzing various types of complex information. For the past six months, the team has worked with the Chisholm Lab at MIT to develop applications within their BigDAWG architecture to fit the specific needs of the lab. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | MIT Lincoln Laboratory | en_US |
dc.relation.ispartofseries | The Bulletin; | |
dc.rights | Attribution-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nd/3.0/us/ | * |
dc.subject | Lincoln Laboratory | en_US |
dc.subject | Supercomputing | en_US |
dc.subject | LLSC | en_US |
dc.subject | Information Sciences | en_US |
dc.subject | BigDAWG | en_US |
dc.title | A Tiny Organism with a Big Data Problem | en_US |
dc.type | Article | en_US |