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IEEE International Conference on Bioinformatics and Biomedicine

作者： Reda Rawi Khalid Kunji Abdelali Haoudi Halima Bensmail Computational Science and Engineering Qatar Computing Research Institute Hamad Bin Khalifa University King Abdullah International Medical Research Center King Abdulaziz Medical City

ISBN: (纸本)9781467368001

HIV-1 Env glycoprotein complex is the key protein that mediates binding and entry of HIV-1 into human host cells. The complex entry process involves three main steps. First, the attachment, the interaction of gp120 and CD4. Second, the coreceptor binding, where gp120 binds the chemokine receptor CCR5 or CXCR4, and finally, the fusion of viral and host cell membranes. Despite the fact that several coordinate structures of HIV-1 Env in unliganded state exist (as well as in complex with CD4, CD4 mimics, or various antibodies, and of gp41 in intermediate and post-fusion state), a comprehensive understanding of structural arrangements and communication within gp120 and gp41 domains during the entry is far from complete. In this study, we applied a direct amino acid interaction detecting method to analyse the function and structure of HIV-1 Env protein sequences representing all group M subtypes. We identified more than 400 coevolving residue pairs within Env, of which the majority are real contacts and proximal in the available coordinate structures, or have functional implications such as receptor binding, variable loop, gp120-gp41, and interdomain interactions. This work provides a new dimension of information in HIV research, important in assisting protein coordinate structure prediction and in designing new and effective entry inhibitors.

关键词： HIV-1 Env Group M subtypes Contact Prediction

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Latest Advances in Theories and Applications of Cognitive Robotics and Brain-Inspired Systems

Latest Advances in Theories and Applications of Cognitive Ro...

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2015 IEEE Advanced Information Technology,Electronic and Automation Control Conference(IAEAC 2015)

作者： YingXU Wang International Institute of Cognitive Informatics and Cognitive Computing(ICIC) Laboratory for Computational Intelligence Cognitive Systemsand Software Science Dept.of Electrical and Computer Engineering Schulich School of Engineering and Hotchkiss Brain Institute University of Calgary

In the new era of intelligence revolution beyond information and computing revolutions,a brain-like intelligent system is emerging known as cognitive robots.A cognitive robot is an autonomous system that is capable of perception,learning,and inference mimicking the cognitive mechanisms of the brain by computational *** robotics is a discipline that studies theories,mathematical means,implementations,and engineering applications of cognitive *** theoretical foundations of cognitive robotics are underpinned in brain science,cognitive science,abstract intelligence,knowledge science,intelligence science,cognitive linguistics,and denotational *** keynote lecture presents the latest advances in theories and applications of cognitive robotics and brain-inspired *** theoretical framework of cognitive robotics and its denotational mathematical means such as concept algebra,semantic algebra,behavioral process algebra,and inference algebra are *** challenges in cognitive robotics are formally studied on what the necessary and sufficient intelligent behaviors of cognitive robots are,and what distinguish the intelligent capabilities of cognitive robots from their imperative *** structural and functional models of cognitive robots are explored at the intelligent layers of imperative,autonomic,and cognitive *** progress in cognitive robotics has led to the development of cognitive systems,nextgeneration computers,and cognitive machine learning engines,as well as the growth of contemporary knowledge-based industries.

关键词： Cognitive robotics cognitive informatics cognitive computing abstract intelligence computational intelligence denotational mathematics concept algebra semantic algebra brain science neuroinformatics cognitive machine learning cognitive knowledge base artificial intelligence and cognitive systems

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Packet-oriented streamline tracing on modern SIMD architectures

Packet-oriented streamline tracing on modern SIMD architectu...

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15th Eurographics Symposium on Parallel Graphics and Visualization, EG PGV 2015

作者： Hentschel, B. Göbbert, J.H. Klemm, M. Springer, P. Schnorr, A. Kuhlen, T.W. Virtual Reality Group RWTH Aachen University Germany JARA - High Performance Computing Germany Software and Services Group Intel GmbH Germany Aachen Institute for Advanced Study in Computational Engineering Science RWTH Aachen University Germany Jülich Supercomputing Centre Forschungszentrum Jülich GmbH Germany HPAC - High Performance and Automatic Computing RWTH Aachen University Germany

ISBN: (纸本)9783905674811

The advection of integral lines is an important computational kernel in vector field visualization. We investigate how this kernel can profit from vector (SIMD) extensions in modern CPUs. As a baseline, we formulate a streamline tracing algorithm that facilitates auto-vectorization by an optimizing compiler. We analyze this algorithm and propose two different optimizations. Our results show that particle tracing does not per se benefit from SIMD computation. Based on a careful analysis of the auto-vectorized code, we propose an optimized data access routine and a re-packing scheme which increases average SIMD efficiency. We evaluate our approach on three different, turbulent flow fields. Our optimized approaches increase integration performance up to 5:6 over our baseline measurement. We conclude with a discussion of current limitations and aspects for future work. © The Eurographics Association 2015.

关键词： Program processors

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Correction to: Meeting report from the fourth meeting of the computational Modeling in Biology Network (COMBINE)

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Standards in genomic sciences 2018年第1期13卷 17页

作者： Dagmar Waltemath Frank T Bergmann Claudine Chaouiya Tobias Czauderna Padraig Gleeson Carole Goble Martin Golebiewski Michael Hucka Nick Juty Olga Krebs Nicolas Le Novère Huaiyu Mi Ion I Moraru Chris J Myers David Nickerson Brett G Olivier Nicolas Rodriguez Falk Schreiber Lucian Smith Fengkai Zhang Eric Bonnet 1Department of Systems Biology and Bioinformatics University of Rostock Rostock Germany. 2Department of Computing and Mathematical Sciences California Institute of Technology Pasadena CA USA. 4Instituto Gulbenkian de Ciência - IGC Rua da Quinta Grande Oeiras Portugal. 3IPK Gatersleben Gatersleben Germany. 5Department of Neuroscience Physiology and Pharmacology University College London London UK. 6School of Computer Science The University of Manchester Manchester UK. 7Heidelberg Institute for Theoretical Studies Heidelberg Germany. 8EMBL-European Bioinformatics Institute Wellcome Trust Genome Campus Hinxton Cambridge UK. 14The Babraham Institute Babraham Research Campus Cambridge UK. 9Department of preventive medicine Keck School of Medicine University of Southern California Los Angeles CA USA. 10Center for Cell Analysis and Modeling University of Connecticut Health Center Farmington CT USA. 11Department of Electrical and Computer Engineering University of Utah Salt Lake City USA. 12Auckland Bioengineering Institute University of Auckland Auckland New Zealand. 13Systems Bioinformatics VU University Amsterdam Amsterdam The Netherlands. 15Martin Luther University Halle-Wittenberg Halle Germany. 16Monash University Melbourne Australia. Computational Biology Unit Laboratory of Systems Biology National Institute of Allergy and Infectious Diseases NIH Bethesda MD USA. 18Institut Curie Paris France. INSERM U900 75248 Paris France. 20Mines ParisTech 77300 Fontainebleau Paris France.

[This corrects the article DOI: 10.4056/sigs.5279417.].

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Towards Parallel Large-Scale Genomic Prediction by Coupling Sparse and Dense Matrix Algebra

Towards Parallel Large-Scale Genomic Prediction by Coupling ...

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Euromicro Conference on Parallel, Distributed and Network-Based Processing

作者： Arne De Coninck Drosos Kourounis Fabio Verbosio Olaf Schenk Bernard De Baets Steven Maenhout Jan Fostier Universiteit Gent Gent BE Advanced Computing Laboratory Institute of Computational Science USI Lugano Switzerland Progeno B-9052 Zwijnaarde Belgium Faculty of Engineering and Architecture Ghent University - iMinds Belgium

Genomic prediction for plant breeding requires taking into account environmental effects and variations of genetic effects across environments. The latter can be modelled by estimating the effect of each genetic marker in every possible environmental condition, which leads to a huge amount of effects to be estimated. Nonetheless, the information about these effects is only sparsely present, due to the fact that plants are only tested in a limited number of environmental conditions. In contrast, the genotypes of the plants are a dense source of information and thus the estimation of both types of effects in one single step would require as well dense as sparse matrix formalisms. This paper presents a way to efficiently apply a high performance computing infrastructure for dealing with large-scale genomic prediction settings, relying on the coupling of dense and sparse matrix algebra.

关键词： Sparse matrices Bioinformatics Genomics Mathematical model computational modeling Predictive models

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A hybrid development platform for evolutionary multi-objective optimization

A hybrid development platform for evolutionary multi-objecti...

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Congress on Evolutionary Computation

作者： Ruimin Shen Jinhua Zheng Miqing Li School of Mathematics & Computational Science Xiangtan University Hunan China Institute of Information Engineering Xiangtan University Hunan China Department of Information Systems & Computing Brunel University Uxbridge Middlesex U. K

ISBN: (纸本)9781479974931

This paper introduces an optimization template library (OTL), a cross-platform C++ template library for multiobjective optimization. OTL has an object-oriented architecture, which allows that different modules can be arbitrarily combined with each other. Moreover, the C++ template technique is used to increase the flexibility of OTL. Meanwhile, generic programming is widely used in OTL, and the generic algorithms can be used to process different data structures. However, compared with C++, the Python script is more suitable for building the experimental platform. To ensure that all attributes of the experimental results can be fully maintained, a database is used to store the experimental data. Moreover, batch experiments can be easily defined in a set of configuration files; thus, the experiments can be executed automatically without human intervention. In addition, serial and various parallel execution modes are supported, and the user can easily switch the running mode to distributed computing to increase the computing speed. Finally, a highly customizable data visualization tool is created to play back the data sample stored in the database. From a series of comparative studies, the accuracy and running performance of OTL are verified by the statistical results.

关键词： Optimization Libraries Programming Software Data structures Encoding

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Sequential pattern mining of electronic healthcare reimbursement claims: Experiences and challenges in uncovering how patients are treated by physicians

Sequential pattern mining of electronic healthcare reimburse...

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IEEE International Conference on Big Data

作者： Kunal Malhotra Tanner C. Hobson Silvia Valkova Laura L. Pullum Arvind Ramanathan Computational Science and Engineering Oak Ridge National Laboratory Tennessee USA College of Computing Georgia Institute of Technology Georgia USA IMS Government Solutions Pennsylvania USA Health Data Sciences Institute Oak Ridge National Laboratory Tennessee USA

We examine the use of electronic healthcare reimbursement claims (EHRC) for analyzing healthcare delivery and practice patterns across the United States (US). We show that EHRCs are correlated with disease incidence estimates published by the Centers for Disease Control. Further, by analyzing over 1 billion EHRCs, we track patterns of clinical procedures administered to patients with autism spectrum disorder (ASD), heart disease (HD) and breast cancer (BC) using sequential pattern mining algorithms. Our analyses reveal that in contrast to treating HD and BC, clinical procedures for ASD diagnoses are highly varied leading up to and after the ASD diagnoses. The discovered clinical procedure sequences also reveal significant differences in the overall costs incurred across different parts of the US, indicating a lack of consensus amongst practitioners in treating ASD patients. We show that a data-driven approach to understand clinical trajectories using EHRC can provide quantitative insights into how to better manage and treat patients. Based on our experience, we also discuss emerging challenges in using EHRC datasets for gaining insights into the state of contemporary healthcare delivery and practice in the US.

关键词： Data mining Trajectory Diseases High definition video Electronic mail

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Large-scale hydrodynamic brownian simulations on multicore and GPU architectures 14

Large-scale hydrodynamic brownian simulations on multicore a...

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2014 Annual Conference on Extreme science and engineering Discovery Environment, XSEDE 2014

作者： Lopez, M. Graham Horton, Mitchel D. Chow, Edmond School of Computational Science and Engineering College of Computing Georgia Institute of Technology Atlanta GA 30332 United States

ISBN: (纸本)9781450328937

We present here ongoing work to produce an implementation of Brownian dynamics simulation using a matrix-free method with hardware accelerators. This work describes the GPU acceleration of a smooth particle-mesh Ewald (SPME) algorithm which is used for the main part of the computation, previously ported to run on Intel Xeon Phi. Copyright 2014 ACM.

关键词： Graphics processing unit

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Identification of Patient Zero in Static and Temporal Networks: Robustness and Limitations

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Physical Review Letters 2015年第24期114卷 248701-248701页

作者： Nino Antulov-Fantulin Alen Lančić Tomislav Šmuc Hrvoje Štefančić Mile Šikić Computational Biology and Bioinformatics Group Division of Electronics Rudjer Bošković Institute Zagreb 10000 Croatia Department of Mathematics Faculty of Science University of Zagreb Zagreb 10000 Croatia Theoretical Physics Division Rudjer Bošković Institute Zagreb 10000 Croatia Catholic University of Croatia Zagreb 10000 Croatia Department of Electronic Systems and Information Processing Faculty of Electrical Engineering and Computing University of Zagreb Zagreb 10000 Croatia Bioinformatics Institute A*STAR Singapore 138671 Republic of Singapore

Detection of patient zero can give new insights to epidemiologists about the nature of first transmissions into a population. In this Letter, we study the statistical inference problem of detecting the source of epidemics from a snapshot of spreading on an arbitrary network structure. By using exact analytic calculations and Monte Carlo estimators, we demonstrate the detectability limits for the susceptible-infected-recovered model, which primarily depend on the spreading process characteristics. Finally, we demonstrate the applicability of the approach in a case of a simulated sexually transmitted infection spreading over an empirical temporal network of sexual interactions.

关键词： EPIDEMICS SEXUALLY transmitted diseases INFERENTIAL statistics MONTE Carlo method ROBUST control

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Analysis of Sparse Quasi-Newton Updates with Positive Definite Matrix Completion

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Journal of the Operations Research Society of China 2014年第1期2卷 39-56页

作者： Yu-Hong Dai Nobuo Yamashita State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering ComputingAcademy of Mathematics and Systems ScienceChinese Academy of SciencesP.O.Box 2719Beijing 100080People’s Republic of China Department of Applied Mathematics and Physics Graduate School of InformaticsKyoto UniversityKyoto 606-8501Japan

Based on the idea of maximum determinant positive definite matrix completion,Yamashita(Math Prog 115(1):1–30,2008)proposed a new sparse quasi-Newton update,called MCQN,for unconstrained optimization problems with sparse Hessian *** exchange of the relaxation of the secant equation,the MCQN update avoids solving difficult subproblems and overcomes the ill-conditioning of approximate Hessian ***,local and superlinear convergence results were only established for the MCQN update with the DFP *** this paper,we extend the convergence result to the MCQN update with the whole Broyden’s convex *** results are also reported,which suggest some efficient ways of choosing the parameter in the MCQN update the Broyden’s family.

关键词： Quasi-Newton method Large-scale problems Sparsity Positive definite matrix completion Superlinear convergence

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