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Showing papers on "Graphical user interface published in 2018"


Journal ArticleDOI
TL;DR: The Tinker software, currently released as version 8, is a modular molecular mechanics and dynamics package written primarily in a standard, easily portable dialect of Fortran 95 with OpenMP extensions, which supports a wide variety of force fields.
Abstract: The Tinker software, currently released as version 8, is a modular molecular mechanics and dynamics package written primarily in a standard, easily portable dialect of Fortran 95 with OpenMP extensions It supports a wide variety of force fields, including polarizable models such as the Atomic Multipole Optimized Energetics for Biomolecular Applications (AMOEBA) force field The package runs on Linux, macOS, and Windows systems In addition to canonical Tinker, there are branches, Tinker-HP and Tinker-OpenMM, designed for use on message passing interface (MPI) parallel distributed memory supercomputers and state-of-the-art graphical processing units (GPUs), respectively The Tinker suite also includes a tightly integrated Java-based graphical user interface called Force Field Explorer (FFE), which provides molecular visualization capabilities as well as the ability to launch and control Tinker calculations

800 citations


Journal ArticleDOI
07 Mar 2018-eLife
TL;DR: New open-source software called cisTEM (computational imaging system for transmission electron microscopy) for the processing of data for high-resolution electron cryo-microscopy and single-particle averaging is developed, optimized to enable processing of typical datasets on a high-end, CPU-based workstation in half a day or less, comparable to GPU-accelerated processing.
Abstract: We have developed new open-source software called cisTEM (computational imaging system for transmission electron microscopy) for the processing of data for high-resolution electron cryo-microscopy and single-particle averaging. cisTEM features a graphical user interface that is used to submit jobs, monitor their progress, and display results. It implements a full processing pipeline including movie processing, image defocus determination, automatic particle picking, 2D classification, ab-initio 3D map generation from random parameters, 3D classification, and high-resolution refinement and reconstruction. Some of these steps implement newly-developed algorithms; others were adapted from previously published algorithms. The software is optimized to enable processing of typical datasets (2000 micrographs, 200 k - 300 k particles) on a high-end, CPU-based workstation in half a day or less, comparable to GPU-accelerated processing. Jobs can also be scheduled on large computer clusters using flexible run profiles that can be adapted for most computing environments. cisTEM is available for download from cistem.org.

746 citations



Journal ArticleDOI
TL;DR: CCP4i2 is a graphical user interface to the CCP4 (Collaborative Computational Project, Number 4) software suite and a Python language framework for software automation.
Abstract: The CCP4 (Collaborative Computational Project, Number 4) software suite for macromolecular structure determination by X-ray crystallography groups brings together many programs and libraries that, by means of well established conventions, interoperate effectively without adhering to strict design guidelines. Because of this inherent flexibility, users are often presented with diverse, even divergent, choices for solving every type of problem. Recently, CCP4 introduced CCP4i2, a modern graphical interface designed to help structural biologists to navigate the process of structure determination, with an emphasis on pipelining and the streamlined presentation of results. In addition, CCP4i2 provides a framework for writing structure-solution scripts that can be built up incrementally to create increasingly automatic procedures.

340 citations




Proceedings ArticleDOI
19 Jun 2018
TL;DR: It is shown that deep learning methods can be leveraged to train a model end-to-end to automatically reverse engineer user interfaces and generate code from a single input image with over 77% of accuracy for three different platforms.
Abstract: Transforming a graphical user interface screenshot created by a designer into computer code is a typical task conducted by a developer in order to build customized software, websites, and mobile applications. In this paper, we show that deep learning methods can be leveraged to train a model end-to-end to automatically reverse engineer user interfaces and generate code from a single input image with over 77% of accuracy for three different platforms (i.e. iOS, Android and web-based technologies).

179 citations







Proceedings ArticleDOI
19 Apr 2018
TL;DR: Data Illustrator is proposed, a novel visualization framework that extends interaction techniques in modern vector design tools for direct manipulation of visualization configurations and parameters and demonstrates the expressive power of the approach through a variety of examples.
Abstract: Building graphical user interfaces for visualization authoring is challenging as one must reconcile the tension between flexible graphics manipulation and procedural visualization generation based on a graphical grammar or declarative languages. To better support designers' workflows and practices, we propose Data Illustrator, a novel visualization framework. In our approach, all visualizations are initially vector graphics; data binding is applied when necessary and only constrains interactive manipulation to that data bound property. The framework augments graphic design tools with new concepts and operators, and describes the structure and generation of a variety of visualizations. Based on the framework, we design and implement a visualization authoring system. The system extends interaction techniques in modern vector design tools for direct manipulation of visualization configurations and parameters. We demonstrate the expressive power of our approach through a variety of examples. A qualitative study shows that designers can use our framework to compose visualizations.




Journal ArticleDOI
TL;DR: Using a popular video game engine, Unity, and coupling it with BCI2000, a tool is created that allows users the flexibility to create and modularize aspects of BCI applications for control of IoT devices and VR environments.
Abstract: Brain–computer interfaces (BCIs) have enabled individuals to control devices, such as spellers, robotic arms, drones, and wheelchairs, but often these BCI applications are restricted to research laboratories. With the advent of virtual reality (VR) systems and the Internet of Things (IoT) we can couple these technologies to offer real-time control of a user’s virtual and physical environment. Likewise, BCI applications are often single-use with user’s having no control outside of the restrictions placed upon the applications at the time of creation. Therefore, there is a need to create a tool that allows users the flexibility to create and modularize aspects of BCI applications for control of IoT devices and VR environments. Using a popular video game engine, Unity, and coupling it with BCI2000, we can create diverse applications that give the end-user additional autonomy during the task at hand. We demonstrate the validity of controlling a Unity-based VR environment and several commercial IoT devices via direct neural interfacing processed through BCI2000.



Journal ArticleDOI
TL;DR: The adoption and use of SynBioHub, a community-driven effort, has the potential to overcome the reproducibility challenge across laboratories by helping to address the current lack of information about published designs.
Abstract: The SynBioHub repository (https://synbiohub.org) is an open-source software project that facilitates the sharing of information about engineered biological systems. SynBioHub provides computational access for software and data integration, and a graphical user interface that enables users to search for and share designs in a Web browser. By connecting to relevant repositories (e.g., the iGEM repository, JBEI ICE, and other instances of SynBioHub), the software allows users to browse, upload, and download data in various standard formats, regardless of their location or representation. SynBioHub also provides a central reference point for other resources to link to, delivering design information in a standardized format using the Synthetic Biology Open Language (SBOL). The adoption and use of SynBioHub, a community-driven effort, has the potential to overcome the reproducibility challenge across laboratories by helping to address the current lack of information about published designs.



Posted ContentDOI
31 Jan 2018-bioRxiv
TL;DR: New open-source software called cisTEM (computational imaging system for transmission electron microscopy) for the processing of data for high-resolution electron cryo-microscopy and single-particle averaging features a graphical user interface that is used to submit jobs, monitor their progress, and display results.
Abstract: We have developed new open-source software called cis TEM (computational imaging system for transmission electron microscopy) for the processing of data for high-resolution electron cryo-microscopy and single-particle averaging. cis TEM features a graphical user interface that is used to submit jobs, monitor their progress, and display results. It implements a full processing pipeline including movie processing, image defocus determination, automatic particle picking, 2D classification, ab-initio 3D map generation from random parameters, 3D classification, and high-resolution refinement and reconstruction. Some of these steps implement newly-developed algorithms; others were adapted from previously published algorithms. The software is optimized to enable processing of typical datasets (2000 micrographs, 200k – 300k particles) on a high-end, CPU-based workstation in half a day or less, comparable to GPU-accelerated processing. Jobs can also be scheduled on large computer clusters using flexible run profiles that can be adapted for most computing environments. cis TEM is available for download from cistem.org.




Journal ArticleDOI
TL;DR: A new graphical user interface for ToxPi (Toxicological Prioritization Index) is presented that provides interactive visualization, analysis, reporting, and portability and introduces several features, from flexible data import formats to similarity-based clustering to options for high-resolution graphical output.
Abstract: Drawing integrated conclusions from diverse source data requires synthesis across multiple types of information. The ToxPi (Toxicological Prioritization Index) is an analytical framework that was developed to enable integration of multiple sources of evidence by transforming data into integrated, visual profiles. Methodological improvements have advanced ToxPi and expanded its applicability, necessitating a new, consolidated software platform to provide functionality, while preserving flexibility for future updates. We detail the implementation of a new graphical user interface for ToxPi (Toxicological Prioritization Index) that provides interactive visualization, analysis, reporting, and portability. The interface is deployed as a stand-alone, platform-independent Java application, with a modular design to accommodate inclusion of future analytics. The new ToxPi interface introduces several features, from flexible data import formats (including legacy formats that permit backward compatibility) to similarity-based clustering to options for high-resolution graphical output. We present the new ToxPi interface for dynamic exploration, visualization, and sharing of integrated data models. The ToxPi interface is freely-available as a single compressed download that includes the main Java executable, all libraries, example data files, and a complete user manual from http://toxpi.org .

Journal ArticleDOI
TL;DR: A major SimVascular (SV) release is introduced that includes a new graphical user interface (GUI) designed to improve user experience and major changes to the software platform and outline features added in this new release.
Abstract: Patient-specific simulation plays an important role in cardiovascular disease research, diagnosis, surgical planning and medical device design, as well as education in cardiovascular biomechanics. simvascular is an open-source software package encompassing an entire cardiovascular modeling and simulation pipeline from image segmentation, three-dimensional (3D) solid modeling, and mesh generation, to patient-specific simulation and analysis. SimVascular is widely used for cardiovascular basic science and clinical research as well as education, following increased adoption by users and development of a GATEWAY web portal to facilitate educational access. Initial efforts of the project focused on replacing commercial packages with open-source alternatives and adding increased functionality for multiscale modeling, fluid-structure interaction (FSI), and solid modeling operations. In this paper, we introduce a major SimVascular (SV) release that includes a new graphical user interface (GUI) designed to improve user experience. Additional improvements include enhanced data/project management, interactive tools to facilitate user interaction, new boundary condition (BC) functionality, plug-in mechanism to increase modularity, a new 3D segmentation tool, and new computer-aided design (CAD)-based solid modeling capabilities. Here, we focus on major changes to the software platform and outline features added in this new release. We also briefly describe our recent experiences using SimVascular in the classroom for bioengineering education.

Journal ArticleDOI
TL;DR: The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms, and targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis.
Abstract: Xi-cam is an extensible platform for data management, analysis and visualization. Xi-cam aims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms. Plugins are available for SAXS/WAXS/GISAXS/GIWAXS, tomography and NEXAFS data. With Xi-cam's `advanced' mode, data processing steps are designed as a graph-based workflow, which can be executed live, locally or remotely. Remote execution utilizes high-performance computing or de-localized resources, allowing for the effective reduction of high-throughput data. Xi-cam's plugin-based architecture targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis. Xi-cam is open-source and cross-platform, and available for download on GitHub.