@proceedings {38176, title = {Computing the Tree of Life: Leveraging the Power of Desktop and Service Grids}, year = {2011}, month = {2011}, type = {10.1109/IPDPS.2011.344}, abstract = {The trend in life sciences research, particularly in molecular evolutionary systematics, is toward larger data sets and ever-more detailed evolutionary models, which can generate substantial computational loads. Over the past several years we have developed a grid computing system aimed at providing researchers the computational power needed to complete such analyses in a timely manner. Our grid system, known as The Lattice Project, was the first to combine two models of grid computing - the service model, which mainly federates large institutional HPC resources, and the desktop model, which harnesses the power of PCs volunteered by the general public. Recently we have developed a "science portal" style web interface that makes it easier than ever for phylogenetic analyses to be completed using GARLI, a popular program that uses a maximum likelihood method to infer the evolutionary history of organisms on the basis of genetic sequence data. This paper describes our approach to scheduling thousands of GARLI jobs with diverse requirements to heterogeneous grid resources, which include volunteer computers running BOINC software. A key component of this system provides a priori GARLI runtime estimates using machine learning with random forests.}, keywords = {(artificial, (mathematics), analysis, BOINC, COMPUTATION, computational, computing, data, Estimation, evolutionary, GARLI, genetic, Grid, GRIDS, handling, heterogeneous, History, HPC, information, intelligence), interface, interfaces, Internet, jobs, lattice, learning, life, likelihood, load, machine, maximum, method, model, molecular, phylogenetic, portal, Portals, power, project, resource, Science, sequence, service, services, sets, software, substantial, system, systematics, tree, TREES, user, Web}, author = {Adam L. Bazinet and Michael P. Cummings} } @proceedings {38367, title = {MDMap: A system for data-driven layout and exploration of molecular dynamics simulations}, year = {2011}, month = {2011}, type = {10.1109/BioVis.2011.6094055}, 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, biomolecular, computing, data, digital, driven, DYNAMICS, exploration, folding, graph, landscapes, Layout, MDMap, method, molecular, processes, simulation, Simulations, space, state, Stochastic, THEORY, time-varying, Trajectory, transition}, author = {Patro, R. and Ip, Cheuk Yiu and Bista, S. and Cho, S. S. and Thirumalai, D. and Varshney, Amitabh} }