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DTSTAMP:20190719T085743Z
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DTSTART;TZID=Europe/Stockholm:20190612T140000
DTEND;TZID=Europe/Stockholm:20190612T143000
UID:submissions.pasc-conference.org_PASC19_sess117_msa219@linklings.com
SUMMARY:Managing High-Throughput Molecular Dynamics Simulation Data
DESCRIPTION:Minisymposium\nComputer Science and Applied Mathematics, Physi
 cs, Life Sciences\n\nManaging High-Throughput Molecular Dynamics Simulatio
 n Data\n\nHospital, Gelpi\n\nMolecular dynamics (MD) simulation has become
  a mature technique to understand the dynamic properties of macromolecules
  at a level (time scales, system sizes) that can be relevant to understand
  biological phenomena. As the time scale and system size increase, so does
  the amount of data generated, which now typically reaches TBs of informat
 ion per simulation. In spite of its importance, the lack of management pro
 cedures makes extremely difficult the maintenance of permanent repositorie
 s where data can be used beyond the initial project-specific analyses. Dif
 ferent efforts have been presented to organize, store and make available M
 D trajectories together with their associated metadata and analysis (1,2).
  We will present the strategy and experiences gained applying Big Data tec
 hnologies, such as NoSQL databases, to the development of these kinds of r
 epositories. They have enabled a most efficient storage and retrieval of i
 nformation, including the possibility of performing global analyses on ext
 ended sets of stored data. The efficiency of MongoDB manager and its GridF
 S associated technology has allowed a direct connection between the inform
 ation stored in the database and graphical user interfaces to represent th
 e data in a useful way. <br />1 Meyer, T. et al. Structure 18, 1399–
 1409 (2010). <br />2 Hospital, A. et al. Nucleic Acids Res 44, D272-8 (201
 6).
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