TY - Generic T1 - MDMap: A system for data-driven layout and exploration of molecular dynamics simulations T2 - Biological Data Visualization (BioVis), 2011 IEEE Symposium on Y1 - 2011 A1 - Patro, R. A1 - Ip, Cheuk Yiu A1 - Bista, S. A1 - Cho, S. S. A1 - Thirumalai, D. A1 - Varshney, Amitabh KW - Biology KW - biomolecular KW - computing KW - data KW - digital KW - driven KW - DYNAMICS KW - exploration KW - folding KW - graph KW - landscapes KW - Layout KW - MDMap KW - method KW - molecular KW - processes KW - simulation KW - Simulations KW - space KW - state KW - Stochastic KW - THEORY KW - time-varying KW - Trajectory KW - transition AB - 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. JA - Biological Data Visualization (BioVis), 2011 IEEE Symposium on ER - TY - JOUR T1 - Microbial oceanography in a sea of opportunity JF - NatureNature Y1 - 2009 A1 - Bowler, Chris A1 - Karl, David M. A1 - Rita R. Colwell KW - Astronomy KW - astrophysics KW - Biochemistry KW - Bioinformatics KW - Biology KW - biotechnology KW - cancer KW - cell cycle KW - cell signalling KW - climate change KW - Computational Biology KW - development KW - developmental biology KW - DNA KW - drug discovery KW - earth science KW - ecology KW - environmental science KW - Evolution KW - evolutionary biology KW - functional genomics KW - Genetics KW - Genomics KW - geophysics KW - immunology KW - interdisciplinary science KW - life KW - marine biology KW - materials science KW - medical research KW - medicine KW - metabolomics KW - molecular biology KW - molecular interactions KW - nanotechnology KW - Nature KW - neurobiology KW - neuroscience KW - palaeobiology KW - pharmacology KW - Physics KW - proteomics KW - quantum physics KW - RNA KW - Science KW - science news KW - science policy KW - signal transduction KW - structural biology KW - systems biology KW - transcriptomics AB - Plankton use solar energy to drive the nutrient cycles that make the planet habitable for larger organisms. We can now explore the diversity and functions of plankton using genomics, revealing the gene repertoires associated with survival in the oceans. Such studies will help us to appreciate the sensitivity of ocean systems and of the ocean's response to climate change, improving the predictive power of climate models. VL - 459 SN - 0028-0836 ER -