29 research outputs found

    Networking for Historical Justice: The Application of Graph Database Management Systems to Network Analysis Projects and the Case Study of the Reparation Movement for Japanese Colonial and Wartime Atrocities

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    This is an ongoing project to digitize reparation lawsuits against Japanese colonial and wartime atrocities (most famously the "comfort women" system and Nanjing Massacre) into a graph database. Information about the lawsuits is taken from publicly available sources such as the 日本戦後補償裁判総覧 (http://justice.skr.jp/souran/souran-jp-web.htm), digitized, processed, and exported as cypher codes executable by graph database management or processing systems such as Neo4j. The database seeks to not only preserve historical materials produced in this transnational movement but also aid academic research and teaching of it. The project explores the applicability of graph database management systems to network analysis research and teaching in the field of digital humanities. By inputting the data about lawsuits and lawyers in the movement into a graph database, the project demonstrates the advantages of managing network data in graph database structure over relational database structure, which is the mainstream in network analysis research, in terms of scalability, modifiability, intuitive visibility, and query efficiency. The all-plain.cypher file can be loaded into graph database systems like Neo4j (https://sandbox.neo4j.com) to generate the database. The all data Kineviz-graphxr DATE.graphxr file can be loaded into the web-based graph visualization and processing tool GraphXR(https://graphxr.kineviz.com/register) with an account

    Structure-based model for light-harvesting properties of nucleic acid nanostructures

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    Programmed self-assembly of DNA enables the rational design of megadalton-scale macromolecular assemblies with sub-nanometer scale precision. These assemblies can be programmed to serve as structural scaffolds for secondary chromophore molecules with light-harvesting properties. Like in natural systems, the local and global spatial organization of these synthetic scaffolded chromophore systems plays a crucial role in their emergent excitonic and optical properties. Previously, we introduced a computational model to predict the large-scale 3D solution structure and flexibility of nucleic acid nanostructures programmed using the principle of scaffolded DNA origami. Here, we use Förster resonance energy transfer theory to simulate the temporal dynamics of dye excitation and energy transfer accounting both for overall DNA nanostructure architecture as well as atomic-level DNA and dye chemical structure and composition. Results are used to calculate emergent optical properties including effective absorption cross-section, absorption and emission spectra and total power transferred to a biomimetic reaction center in an existing seven-helix double stranded DNA-based antenna. This structure-based computational framework enables the efficient in silico evaluation of nucleic acid nanostructures for diverse light-harvesting and photonic applications.United States. Office of Naval Research (ONR N000141210621)United States. Army Research Office (ARO MURI W911NF1210420

    Lattice-free prediction of three-dimensional structure of programmed DNA assemblies

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    DNA can be programmed to self-assemble into high molecular weight 3D assemblies with precise nanometer-scale structural features. Although numerous sequence design strategies exist to realize these assemblies in solution, there is currently no computational framework to predict their 3D structures on the basis of programmed underlying multi-way junction topologies constrained by DNA duplexes. Here, we introduce such an approach and apply it to assemblies designed using the canonical immobile four-way junction. The procedure is used to predict the 3D structure of high molecular weight planar and spherical ring-like origami objects, a tile-based sheet-like ribbon, and a 3D crystalline tensegrity motif, in quantitative agreement with experiments. Our framework provides a new approach to predict programmed nucleic acid 3D structure on the basis of prescribed secondary structure motifs, with possible application to the design of such assemblies for use in biomolecular and materials science.United States. Office of Naval Research (ONR N000141210621)National Science Foundation (U.S.) (NSF-DMREF Program CMMI1334109

    Structure and conformational dynamics of scaffolded DNA origami nanoparticles

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    Synthetic DNA is a highly programmable nanoscale material that can be designed to self-assemble into 3D structures that are fu lly determined by underlying Watson-Crick base pairing. The double crossover (DX) design motif has demonstrated versatility in synthesizing arbitrary DNA nanoparticles on the 5- 100 nm scale for diverse applications in biotechnology. Prior computational investigations of these assemblies include all-atom and coarse-grained modeling, but modeling their conformational dynamics remains challenging due to their long relaxation times and associated computational cost. We apply all-atom molecular dynamics and coarse-grained finite element modeling to DX-based nanoparticles to elucidate their fine-scale and global conformational structure and dynamics. We use our coarsegrained model with a set of secondary structural motifs to predict the equilibrium solution structures of 45 DX-based DNA origami nanoparticles including a tetrahedron, octahedron, icosahedron, cuboctahedron and reinforced cube. Coarse-grained models are compared with 3D cryo-electron microscopy density maps for these five DNA nanoparticles and with all-atom molecular dynamics simulations for the tetrahedron and octahedron. Our results elucidate non-intuitive atomic-level structural details of DXbased DNA nanoparticles, and offer a general framework for efficient computational prediction of global and local structural andmechanical properties of DXbased assemblies that are inaccessible to all-atom based models alone.United States. Office of Naval Research (Grant N00014-12-1-0621)United States. Army Research Office (Grant W911NF1210420)National Science Foundation (U.S.) (Grant 1560425)United States. Office of Naval Research (Grant N00014-13-1-0664)United States. Office of Naval Research (Grant N00014-15-1-2830

    Computational and Theoretical Analysis of Influenza Virus Evolution and Immune System Dynamics

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    Influenza causes annual global epidemics and severe morbidity and mortality. The influenza virus evolves to escape from immune system antibodies that bind to it. The immune system produces influenza virus specific antibodies by VDJ recombination and somatic hypermutation. In this dissertation, we analyze the mechanism of influenza virus evolution and immune system dynamics using theoretical modeling and computational simulation. The first half of this thesis discusses influenza virus evolution. The epidemiological data inspires a novel sequence-based antigenic distance measure for subtypes H1N1 and H3N2 virus, which are superior to the conventional measure using hemagglutination inhibition assay. Historical influenza sequences show that the selective pressure increases charge in immunodominant epitopes of the H3 hemagglutinin influenza protein. Statistical mechanics and high-performance computing technology predict fixation tendencies of the H3N2 influenza virus by free energy calculation. We introduce the notion of entropy from physics and informatics to identify the epitope regions of H1-subtype influenza A with application to vaccine efficacy. We also use entropy to quantify selection and diversity in viruses with application to the hemagglutinin of H3N2 influenza. Using the bacterial E. coli as a model, we show the evidence for recombination contributing to the evolution of extended spectrum β-lactamases (ES-BLs) in clinical isolates. A guinea pig experiment supports the discussion on influenza virus evolution. The second half of the thesis discusses immune system dynamics. We design a two-scale model to describe correlation in B cell VDJ usage of zebrafish. We also introduce a dynamical system to model original antigenic sin in influenza. This dissertation aims to help researchers understand the interaction between influenza virus and the immune system with a quantitative approach

    Understanding original antigenic sin in influenza with a dynamical system.

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    Original antigenic sin is the phenomenon in which prior exposure to an antigen leads to a subsequent suboptimal immune response to a related antigen. Immune memory normally allows for an improved and rapid response to antigens previously seen and is the mechanism by which vaccination works. I here develop a dynamical system model of the mechanism of original antigenic sin in influenza, clarifying and explaining the detailed spin-glass treatment of original antigenic sin. The dynamical system describes the viral load, the quantities of healthy and infected epithelial cells, the concentrations of naïve and memory antibodies, and the affinities of naïve and memory antibodies. I give explicit correspondences between the microscopic variables of the spin-glass model and those of the present dynamical system model. The dynamical system model reproduces the phenomenon of original antigenic sin and describes how a competition between different types of B cells compromises the overall effect of immune response. I illustrate the competition between the naïve and the memory antibodies as a function of the antigenic distance between the initial and subsequent antigens. The suboptimal immune response caused by original antigenic sin is observed when the host is exposed to an antigen which has intermediate antigenic distance to a second antigen previously recognized by the host's immune system

    Demand Driven Research Support in the Library: A Case Study in History and Digital Humanities

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    This section presents the timeline of instruction support, research consultation, and collection development offered by faculty librarians Molly Castro and Christopher M. Jimenez to support History Professor Kyle Pan and History grad student Noel Hernandez. Noel’s dissertation research and accompanying digital history project on the history of rock bands in Latin America serve as a case study on demand driven research support from librarians in both Information & Research Services and Digital Humanities

    Inferring transient particle transport dynamics in live cells

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    Live-cell imaging and particle tracking provide rich information on mechanisms of intracellular transport. However, trajectory analysis procedures to infer complex transport dynamics involving stochastic switching between active transport and diffusive motion are lacking. We applied Bayesian model selection to hidden Markov modeling to infer transient transport states from trajectories of mRNA-protein complexes in live mouse hippocampal neurons and metaphase kinetochores in dividing human cells. The software is available at http://hmm-bayes.org/.National Institutes of Health (U.S.)National Institute of Mental Health (U.S.) (Grant U01 MH106011)National Science Foundation (U.S.). Physics of Living Systems (Grant PHY 1305537)Leukemia & Lymphoma Society of America (Scholar Award)National Institute of General Medical Sciences (U.S.) (Grant GM088313)Austrian Science Fund (Schroedinger Fellowship
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