• DocumentCode
    2537717
  • Title

    MDMap: A system for data-driven layout and exploration of molecular dynamics simulations

  • Author

    Patro, Robert ; Ip, Cheuk Yiu ; Bista, Sujal ; Cho, Samuel S. ; Thirumalai, D. ; Varshney, Amitabh

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Maryland, College Park, MD, USA
  • fYear
    2011
  • fDate
    23-24 Oct. 2011
  • Firstpage
    111
  • Lastpage
    118
  • Abstract
    Contemporary molecular dynamics simulations result in a glut of simulation data, making analysis and discovery a difficult and burdensome task. We present MDMap, a system designed to summarize long-running molecular dynamics (MD) simulations. We represent a molecular dynamics simulation as a state transition graph over a set of intermediate (stable and semi-stable) states. The transitions amongst the states together with their frequencies represent the flow of a biomolecule through the trajectory space. MDMap automatically determines potential intermediate conformations and the transitions amongst them by analyzing the conformational space explored by the MD simulation. MDMap is an automated system to visualize MD simulations as state-transition diagrams, and can replace the current tedious manual layouts of biomolecular folding landscapes with an automated tool. The layout of the representative states and the corresponding transitions among them is presented to the user as a visual synopsis of the long-running MD simulation. We compare and contrast multiple presentations of the state transition diagrams, such as conformational embedding, and spectral, hierarchical, and force-directed graph layouts. We believe this system could provide a road-map for the visualization of other stochastic time-varying simulations in a variety of different domains.
  • Keywords
    biology computing; digital simulation; graph theory; molecular dynamics method; stochastic processes; MDMap; biomolecular folding landscapes; data driven exploration; data driven layout; molecular dynamics simulations; state transition graph; stochastic time-varying simulations; trajectory space; Biological system modeling; Computational modeling; Data visualization; Layout; Proteins; Trajectory; Visualization; Bioinformatics; Clustering; Graph layout; Molecular dynamics; Protein folding; Time varying visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biological Data Visualization (BioVis), 2011 IEEE Symposium on
  • Conference_Location
    Providence, RI
  • Print_ISBN
    978-1-4673-0003-2
  • Type

    conf

  • DOI
    10.1109/BioVis.2011.6094055
  • Filename
    6094055