Single-coordinate-driving method for molecular docking: application to modeling of guest inclusion in cyclodextrin

An extension of the computer program CICADA has been developed that allows us to use the single-coordinate-driving (SCD) method for flexible molecular docking. The docking procedure is composed of three independent space rotations, three independent translations, and the torsions selected by the user. One of the coordinates is driven; the other coordinates are relaxed. This procedure follows low-energy wells on the potential energy surface of the entire system. The program allows us to dock more than one ligand molecule to the receptor. We ran two test examples, docking N,N-dimethylformamide into alpha-cyclodextrin and R-phenoxypropionic acid into beta-cyclodextrin. The test examples showed that the SCD approach is able to overcome high-energy barriers and to cover the entire box within which the search is performed. The limitations of molecular dynamics docking in comparison with our approach also are discussed. The philosophy of the newly developed approach is not only to find the best dock for the receptor-ligand(s) system, but also to describe all the important binding modes and provide a good starting point for studying the dynamics within the cavity during the docking process.     

Multisensory VR interaction for protein-docking in the CoRSAIRe project

Proteins take on their function in the cell by interacting with other proteins or biomolecular complexes. To study this process, computational methods, collectively named protein docking, are used to predict the position and orientation of a protein ligand when it is bound to a protein receptor or enzyme, taking into account chemical or physical criteria. This process is intensively studied to discover new biological functions for proteins and to better understand how these macromolecules take on these functions at the molecular scale. Pharmaceutical research also employs docking techniques for a variety of purposes, most notably in the virtual screening of large databases of available chemicals to select likely molecular candidates for drug design. The basic hypothesis of our work is that Virtual Reality (VR) and multimodal interaction can increase efficiency in reaching and analysing docking solutions, in addition to fully a computational docking approach. To this end, we conducted an ergonomic analysis of the protein–protein current docking task as it is carried out today. Using these results, we designed an immersive and multimodal application where VR devices, such as the three-dimensional mouse and haptic devices, are used to interactively manipulate two proteins to explore possible docking solutions. During this exploration, visual, audio, and haptic feedbacks are combined to render and evaluate chemical or physical properties of the current docking configuration.     

Proxy‐guided Image‐based Rendering for Mobile Devices

VR headsets and hand‐held devices are not powerful enough to render complex scenes in real‐time. A server can take on the rendering task, but network latency prohibits a good user experience. We present a new image‐based rendering (IBR) architecture for masking the latency. It runs in real‐time even on very weak mobile devices, supports modern game engine graphics, and maintains high visual quality even for large view displacements. We propose a novel server‐side dual‐view representation that leverages an optimally‐placed extra view and depth peeling to provide the client with coverage for filling disocclusion holes. This representation is directly rendered in a novel wide‐angle projection with favorable directional parameterization. A new client‐side IBR algorithm uses a pre‐transmitted level‐of‐detail proxy with an encaging simplification and depth‐carving to maintain highly complex geometric detail. We demonstrate our approach with typical VR / mobile gaming applications running on mobile hardware. Our technique compares favorably to competing approaches according to perceptual and numerical comparisons.     

CAVE and fishtank virtual-reality displays: a qualitative and quantitative comparison

We present the results from a qualitative and quantitative user study comparing fishtank virtual-reality (VR) and CAVE displays. The results of the qualitative study show that users preferred the fishtank VR display to the CAVE system for our scientific visualization application because of perceived higher resolution, brightness and crispness of imagery, and comfort of use. The results of the quantitative study show that users performed an abstract visual search task significantly more quickly and more accurately on the fishtank VR display system than in the CAVE. The same study also showed that visual context had no significant effect on task performance for either of the platforms. We suggest that fishtank VR displays are more effective than CAVEs for applications in which the task occurs outside the user's reference frame, the user views and manipulates the virtual world from the outside in, and the size of the virtual object that the user interacts with is smaller than the user's body and fits into the fishtank VR display. The results of both studies support this proposition.     

Automatic printed circuit board routeing with intermediate control of the tracking: APRICOT

For several years computers have been used to produce artwork for printed circuit board manufacturer in basically two different modes.In the automatic mode the computer decides most, if not all, of the track routes and relies on the human to add the unrouted connections. This can be done in an essentially offline manner but it is error-prone.In the interactive mode, which may follow the application of an automatic program, the unrouted connections are manipulated on a graphical display. This is essentially an error-free process but it is performed online.This paper describes a new approach to automatic routeing that allow ‘error-free’ manipulation of the routeing in an offline manner.The automatic routine uses a planned, as opposed to a search, technique and this allows intermediate control (offline) of the automatic routeing process. It also enables the user to change component positions at any time during the routeing process in an offline mode.     

Tracing the executions of concurrent programs

Checking the reliability of software is an ever growing challenge. Fully automatic tools that attempt to cover the entire state space often fail because of state explosion. We present instead a toolset that employs some less-ambitious but useful methods to assist in software debugging. The toolset provides an automatic translation of the code into visual flowcharts, allowing the user to interactively select execution paths. It assists the user by calculating path conditions and exploring the neighborhood of the paths. It also allows the user to interactively step through the execution of the program, directed by temporal formulas interpreted over finite sequences. We will show several different ways of using these capabilities for debugging sequential and concurrent programs.     

Immersive structural biology: a new approach to hybrid modeling of macromolecular assemblies

Advanced biophysical imaging techniques, such as cryo-electron microscopy or tomography, enable 3D volumetric reconstructions of large macromolecular complexes in a near-native environment. However, pure volumetric data is insufficient for a detailed understanding of the underlying protein–protein interactions. This obstacle can be overcome by assembling an atomic model of the whole protein complex from known atomic structures, which are available from either X-ray crystallography or homology modeling. Due to many factors such as noise, conformational variability, experimental artifacts, and inexact model structures, existing automatic docking procedures are known to report false positives for a significant number of cases. The present paper focuses on a new technique to combine an offline exhaustive search algorithm with interactive visualization, collision detection, and haptic rendering. The resulting software system is highly immersive and allows the user to efficiently solve even difficult multi-resolution docking problems. Stereoscopic viewing, combined with head tracking and force feedback, generates an ideal virtual environment for true interaction with and solution of hybrid biomolecular modeling problems.     

A Study on New Virtual Reality System in Maze Terrain

This study proposes the maze virtual reality (MVR) system, which is designed to provide new immersive virtual reality (VR) experiences by generating a maze and an event-based maze environment. The MVR system consists of a maze generation technique based on mazemap, which we additionally propose for the automatic generation of diverse maze patterns, event-enhancing immersion, reducing VR sickness, and interactions. First, we present a finite algorithm that automatically generates diverse maze patterns from the user perspective and implements mazemap for automated three-dimensional (3D) terrain generation from a 2D maze pattern. Then, we present optimized events for the maze environment by providing users with deeper immersion and minimized VR sickness. The design procedure is divided into two elements: an automatic structure for arranging predefined events based on maze pattern analysis and a manual operation module. In addition, a Leap Motion-based interactive scheme is implemented for deeper immersion when the user moves in a limited space, while improving object control. Finally, experiments were conducted to analyze user satisfaction with the MVR system, the psychological impact of the continuous mazemap input, and the effects of the event-based environment on immersion enhancement and VR sickness reduction.     

User-level failure detection and auto-recovery of parallel programs in HPC systems

As the mean-time-between-failures (MTBF) continues to decline with the increasing number of components on large-scale high performance computing (HPC) systems, program failures might occur during the execution period with high probability. Ensuring successful execution of the HPC programs has become an issue that the unprivileged users should be concerned. From the user perspective, if the program failure cannot be detected and handled in time, it would waste resources and delay the progress of program execution. Unfortunately, the unprivileged users are unable to perform program state checking due to execution control by the job management system as well as the limited privilege. Currently, automated tools for supporting user-level failure detection and autorecovery of parallel programs in HPC systems are missing. This paper proposes an innovative method for the unprivileged user to achieve failure detection of job execution and automatic resubmission of failed jobs. The state checker in our method is encapsulated as an independent job to reduce interference with the user jobs. In addition, we propose a dual-checker mechanism to improve the robustness of our approach.We implement the proposed method as a tool named automatic re-launcher (ARL) and evaluate it on the Tianhe-2 system. Experiment results show that ARL can detect the execution failures effectively on Tianhe-2 system. In addition, the communication and performance overhead caused by ARL is negligible. The good scalability of ARL makes it applicable for large-scale HPC systems.     

Visualization and analysis using virtual reality

Current virtual reality technologies have not yet crossed the threshold of usability. Not surprisingly, VR has so far shown more promise than practical applications. Yet the promise looks bright for fields such as data visualization and analysis. For such problems, VR offers a natural interface between human and computer that will simplify complicated manipulations of the data. It also provides an opportunity to rely on the interplay of combined senses rather than on a single or even dominant sense. Still, we cannot yet say whether VR is better than other visualization and analysis approaches for certain classes of data and, if so, by how much. The payoff will come not for those applications or tasks for which VR is merely better, even if significantly, but for those applications or tasks for which it offers some unique advantage unavailable otherwise. To answer these questions, we embarked on a multipronged program involving the Graphics, Visualization. and Usability (GVU) Center, the Office of Information Technology Scientific Visualization Lab. and other research groups at Georgia Tech. Integration is mandatory since these questions involve basic considerations: how immersive environments affect user interfaces and human-computer interactions; the ranges and capabilities of sensors; computer graphics and the VR optical system; and applications' needs. We describe some of our results     

GVSS: A High Throughput Drug Discovery Service of Avian Flu and Dengue Fever for EGEE and EUAsiaGrid

In the study of Biomedicines, molecular docking simulation is a common method for predicting potential interacting complexes of small molecules in protein binding sites. However, it is a time-consuming process to search exhaustively all correct conformations of a compound. This study demonstrates how massive molecular docking benefit from state-of-the-art Grid technology. Providing intensive computing power and effective data management, the production e-infrastructure (such as EGEE and EUAsiaGrid) enables opportunities for in-silico drug discovery on the neglected and emerging diseases, for instance, avian influenza and dengue fever. In this study, Grid Application Platform (GAP) and GAP-enabled Virtual Screening Service (GVSS) were developed with the docking engine of the Autodock 3.0.5. A JAVA-based graphical user interface and the GAP allow end-users to specify target and compound library, set up docking parameters, monitor docking jobs and computing resources, visualize and refine docking results, and finally download the final results. To provide a more user-friendly Grid service, GVSS was designed for conducting large-scale molecular docking more easily.     

上机卡制作管理系统的自动化设计

针对目前学生上机卡管理系统存在的问题,设计开发了上机卡制作管理系统,该系统主要包括应用程序设计、功能模块设计、数据库设计等。可以实现自动生成基本信息数据库、用户权限管理、基本信息查询、上机卡制作、补办信息查询等功能。     

Modeling multiple interactions with a Markov random field in query expansion for session search

How to automatically understand and answer users' questions (eg, queries issued to a search engine) expressed with natural language has become an important yet difficult problem across the research fields of information retrieval and artificial intelligence. In a typical interactive Web search scenario, namely, session search, to obtain relevant information, the user usually interacts with the search engine for several rounds in the forms of, eg, query reformulations, clicks, and skips. These interactions are usually mixed and intertwined with each other in a complex way. For the ideal goal, an intelligent search engine can be seen as an artificial intelligence agent that is able to infer what information the user needs from these interactions. However, there still exists a big gap between the current state of the art and this goal. In this paper, in order to bridge the gap, we propose a Markov random field–based approach to capture dependence relations among interactions, queries, and clicked documents for automatic query expansion (as a way of inferring the information needs of the user). An extensive empirical evaluation is conducted on large‐scale web search data sets, and the results demonstrate the effectiveness of our proposed models.     

Intelligent virtual environments for virtual reality art

The development of virtual reality (VR) art installations is faced with considerable difficulties, especially when one wishes to explore complex notions related to user interaction. We describe the development of a VR platform, which supports the development of such installations, from an art+science perspective. The system is based on a CAVE™-like immersive display using a game engine to support visualisation and interaction, which has been adapted for stereoscopic visualisation and real-time tracking. In addition, some architectural elements of game engines, such as their reliance on event-based systems have been used to support the principled definition of alternative laws of Physics. We illustrate this research through the development of a fully implemented artistic brief that explores the notion of causality in a virtual environment. After describing the hardware architecture supporting immersive visualisation we show how causality can be redefined using artificial intelligence technologies inspired from action representation in planning and how this symbolic definition of behaviour can support new forms of user experience in VR.     

CLPGUI: A Generic Graphical User Interface for Constraint Logic Programming

CLPGUI is a generic graphical user interface for visualizing and controlling the execution of constraint logic programs. CLPGUI has been designed to be used in different contexts: initially for teaching purposes, then for debugging complex programs of real-world scale, and recently for developing end-user interfaces. The challenge of developing a tool which is generic w.r.t. both the constraint logic programming system and the visualizers, is addressed by a client-server architecture for connecting a CLP process to a Java-based GUI process, and by a non-intrusive tracing and control method based on annotations in the CLP program. Arbitrary constraints and goals can be posted incrementally from the GUI in an interactive manner, and arbitrary states can be recomputed. We describe several generic 2D and 3D viewers of the variables and of the search tree, and argue that the 3D representation is best-suited to apprehend the shape of large search trees. We also illustrate the use of CLPGUI for developing application-oriented end-user interfaces on two placement problems, one in virtual reality.     

Comparison of Gaze Cursor Input Methods for Virtual Reality Devices

Virtual reality (VR) devices have recently become popular; however, research on input methods for VR devices is lacking. The main input methods of current commercial devices can be classified into two categories: manual selection using a controller and gaze selection. This study aims to derive the optimal input method and timing for VR devices by analyzing the performance of these input methods. A study is conducted in which participants wear a VR headset and select an activated input button from a 3 × 3 array on a VR device with two button sizes and two input methods. The manual selection method exhibits a shorter task completion time but a greater error number compared to the gaze selection method. For the gaze selection method, the task completion time and target search time were shortest when the gaze timing was 1 s. Further, the button size was determined to be statistically significant only when the manual selection method was used. The results of this study can be used as a reference in future VR user experience and product design.     

Peax: Interactive Visual Pattern Search in Sequential Data Using Unsupervised Deep Representation Learning

We present Peax , a novel feature-based technique for interactive visual pattern search in sequential data, like time series or data mapped to a genome sequence. Visually searching for patterns by similarity is often challenging because of the large search space, the visual complexity of patterns, and the user's perception of similarity. For example, in genomics, researchers try to link patterns in multivariate sequential data to cellular or pathogenic processes, but a lack of ground truth and high variance makes automatic pattern detection unreliable. We have developed a convolutional autoencoder for unsupervised representation learning of regions in sequential data that can capture more visual details of complex patterns compared to existing similarity measures. Using this learned representation as features of the sequential data, our accompanying visual query system enables interactive feedback-driven adjustments of the pattern search to adapt to the users’ perceived similarity. Using an active learning sampling strategy, Peax collects user-generated binary relevance feedback. This feedback is used to train a model for binary classification, to ultimately find other regions that exhibit patterns similar to the search target. We demonstrate Peax 's features through a case study in genomics and report on a user study with eight domain experts to assess the usability and usefulness of Peax . Moreover, we evaluate the effectiveness of the learned feature representation for visual similarity search in two additional user studies. We find that our models retrieve significantly more similar patterns than other commonly used techniques.     

Prediction of the multimeric assembly of staphylococcal enterotoxin A with cell-surface protein receptors

Staphylococcal enterotoxin A (SEA) cross-links two class II major histocompatibility complex (MHC) molecules and forms a multimeric assembly with T-cell receptors (TcRs). The X-ray crystal structure of SEA has been solved, yet details describing molecular recognition and association remain unclear. We present a structural model for the interactions of SEA with cell-surface proteins. Molecular docking calculations predicting SEA association with the class II MHC molecule HLA-DR1 were performed by using a rigid-body docking method. Docked orientations were evaluated by a Poisson-Boltzmann model for the electrostatic free energy of binding and the hydrophobic effect calculated from molecular surface areas. We found that the best-scoring SEA conformers for the DR1alpha interface display a binding mode similar to that determined crystallographically for staphylococcal enterotoxin B bound to HLA-DR1. For the zinc-binding site of SEA, docking DR1beta yielded several orientations exhibiting tetrahedral-like coordination geometries. Combining the two interfaces, tetramers were modeled by docking an alphabeta TcR with trimolecular complexes DR1beta-SEA-DR1alpha and SEA-betaDR1alpha-SEA. Our results indicate that the complex DR1beta-SEA-DR1alpha provides a more favorable assembly for the engagement of TcRs, forming SEA molecular contacts that are in accord with reported mutagenesis studies. In contrast, the cooperative association of two SEA molecules on a single DR1 molecule sterically inhibits interactions with TcRs. We suggest that signal transduction stimulated by SEA through large-scale assembly is limited to four or five TcR-(DR1beta-SEA-DR1alpha) tetramers and requires the dimerization of class II MHC molecules, while TcR dimerization is unlikely.     

Automatic and personalized recommendation of TV program contents using sequential pattern mining for smart TV user interaction

Due to the excessive number of TV program contents available at user’s side, efficient access to the preferred TV program content becomes a critical issue for smart TV user interaction. In this paper, we propose an automatic recommendation scheme of TV program contents in sequence using sequential pattern mining (SPM). Motivation of sequential TV program recommendation is based on TV viewer’s behaviors for watching multiple TV program contents in a row. A sequence of TV program contents for recommendation to a target user is constructed based on the features such as an occurrence and net occurrence of frequently watched TV program contents from the similar user group to which the target user belongs. Three types of SPM methods are presented—offline, online and hybrid SPM. To extract sequential patterns of preferably watched TV program contents, we propose a preference weighted normalized modified retrieval rank (PW-NMRR) metric for similar user clustering. In the offline SPM method, we effectively construct the sequential patterns for recommendation using a projection method, which yields good performance for relatively longer sequential patterns. The online SPM method mines sequential patterns online by effectively reflecting the recent preference characteristics of users for TV program contents, which is effective for short-sequence recommendation. The hybrid SPM method combines the offline and online SPM methods. The maximum precisions of 0.877, 0.793 and 0.619 for length-1, -2 and -3 sequence recommendations are obtained from the online, hybrid and offline SPM methods, respectively.