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Highlights from the 11th ISCB Student Council Symposium 2015. Dublin, Ireland. 10 July 2015

BMC bioinformatics 2016年第3期17 Suppl 3卷 95页

作者： Katie Wilkins Mehedi Hassan Margherita Francescatto Jakob Jespersen R. Gonzalo Parra Bart Cuypers Dan DeBlasio Alexander Junge Anupama Jigisha Farzana Rahman Griet Laenen Sander Willems Lieven Thorrez Yves Moreau Nagarajan Raju Sonia Pankaj Chothani C. Ramakrishnan Masakazu Sekijima M. Michael Gromiha Paddy J Slator Nigel J Burroughs Przemysław Szałaj Zhonghui Tang Paul Michalski Oskar Luo Xingwang Li Yijun Ruan Dariusz Plewczynski Giulia Fiscon Emanuel Weitschek Massimo Ciccozzi Paola Bertolazzi Giovanni Felici Pieter Meysman Manu Vanaerschot Maya Berg Hideo Imamura Jean-Claude Dujardin Kris Laukens Westa Domanova James R. Krycer Rima Chaudhuri Pengyi Yang Fatemeh Vafaee Daniel J. Fazakerley Sean J. Humphrey David E. James Zdenka Kuncic Plant Pathology and Plant-Microbe Biology Section School of Integrative Plant Science Cornell University Ithaca USA Graduate Field of Computational Biology Cornell University Ithaca USA School of Computing & Mathematics University of South Wales Cardiff UK Department of Genome Biology for Neurodegenerative Diseases German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association ᅟ Germany Department of Surgery Massachusetts General Hospital The Broad Institute of MIT and Harvard Boston USA Department of Systems Biology Technical University of Denmark Kemitorvet Denmark Protein Physiology Lab Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Buenos Aires Argentina Molecular Parasitology Unit (MPU) Institute of Tropical Medicine Antwerp Belgium Advanced Database Research and Modeling (ADReM) research group University of Antwerp Antwerpen Belgium Department of Computer Science University of Arizona Tucson USA Department of Veterinary Clinical and Animal Sciences Center for non-coding RNA in Technology and Health University of Copenhagen Copenhagen Denmark University College Dublin Dublin Ireland Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Minds Medical IT Department Leuven Belgium Scientific Institute of Public Health (WIV-ISP) Platform of Biotechnology and Molecular Biology (PBB) Brussels Belgium Department of Development and Regeneration @ Kulak KU Leuven Kortrijk Belgium Department of Biotechnology Bhupat and Jyoti Metha School of Biosciences Indian Institute of Technology Madras Chennai India Philips Research North America Briarcliff Manor USA Global Scientific Information and Computing Center (GSIC) Tokyo Institute of Technology Tokyo Japan Systems Biology Centre University of Warwick Senate House Coventry UK Systems Biology Doctoral Training Centre University of Warwick Senate House Coventry UK Center for B

A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laenen, Sander Willems, Lieven Thorrez, Yves Moreau O2 Organism specific protein-RNA recognition: A computational analysis of protein-RNA complex structures from different organisms Nagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael Gromiha O3 Detection of Heterogeneity in Single Particle Tracking Trajectories Paddy J Slator, Nigel J Burroughs O4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecture Przemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz Plewczynski O5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classification Giulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni Felici O6 A Systems Biology Compendium for Leishmania donovani Bart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris Laukens O7 Unravelling signal coordination from large scale phosphorylation kinetic data Westa Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic

关键词： Visceral Leishmaniasis Feature Selection Method Frequent Itemset Mining Leishmania Donovani Student Council

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Accelerating GPGPU architecture simulation

Accelerating GPGPU architecture simulation

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2013 ACM SIGMETRICS International Conference on Measurement and Modeling of computer Systems, SIGMETRICS 2013

作者： Yu, Zhibin Eeckhout, Lieven Goswami, Nilanjan Li, Tao John, Lizy K. Jin, Hai Xu, Chengzhong Shenzhen Institute of Advanced Technology Chinese Academy of Sciences China ELIS Department Ghent University Belgium Intelligent Design of Efficient Architectures Lab. University of Florida Gainesville FL United States Department of Electrical and Computer Engineering University of Texas Austin TX United States Service Computing Technologies and System Lab./Cluster and Grid Computing Lab. HUST Wuhan China Department of Electrical and Computer Engineering Wayne State University MI United States

ISBN: (纸本)9781450319003

Recently, graphics processing units (GPUs) have opened up new opportunities for speeding up general-purpose parallel applications due to their massive computational power and up to hundreds of thousands of threads enabled by programming models such as CUDA. However, due to the serial nature of existing micro-architecture simulators, these massively parallel architectures and workloads need to be simulated sequentially. As a result, simulating GPGPU architectures with typical benchmarks and input data sets is extremely time-consuming. This paper addresses the GPGPU architecture simulation challenge by generating miniature, yet representative GPGPU kernels. We first summarize the static characteristics of an existing GPGPU kernel in a profile, and analyze its dynamic behavior using the novel concept of the divergence flow statistics graph (DFSG). We subsequently use a GPGPU kernel synthesizing framework to generate a miniature proxy of the original kernel, which can reduce simulation time significantly. The key idea is to reduce the number of simulated instructions by decreasing per-thread iteration counts of loops. Our experimental results show that our approach can accelerate GPGPU architecture simulation by a factor of 88X on average and up to 589X with an average IPC relative error of 5.6%.

关键词： Graphics processing unit

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Marginalized denoising autoencoder via graph regularization for domain adaptation

Marginalized denoising autoencoder via graph regularization ...

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Peng, Yong Wang, Shen Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong Unviersity Shanghai 200240 China Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109 United States MoE-Microsoft Key Lab. for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong Unviersity Shanghai 200240 China

ISBN: (纸本)9783642420412

Domain adaptation, which aims to learn domain-invariant features for sentiment classification, has received increasing attention. The underlying rationality of domain adaptation is that the involved domains share some common latent factors. Recently neural network based on Stacked Denoising Auto-Encoders (SDA) and its marginalized version (mSDA) have shown promising results on learning domain-invariant features. To explicitly preserve the intrinsic structure of data, this paper proposes a marginalized Denoising Autoencoders via graph Regularization (GmSDA) in which the autoencoder based framework can learn more robust features with the help of newly incorporated graph regularization. The learned representations are fed into the sentiment classifiers and experiments show that the GmSDA can effectively improve the classification accuracy when comparing with some state-of-the-art models on the cropped Amazon benchmark data set. © Springer-Verlag 2013.

关键词： Classification (of information)

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Structure preserving low-rank representation for semi-supervised face recognition

Structure preserving low-rank representation for semi-superv...

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Peng, Yong Wang, Suhang Wang, Shen Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong Unviersity Shanghai 200240 China Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109 United States MOE-Microsoft Key Lab. for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong Unviersity Shanghai 200240 China

ISBN: (纸本)9783642420412

Constructing an informative and discriminative graph plays an important role in the graph based semi-supervised learning methods. Among these graph construction methods, low-rank representation based graph, which calculates the edge weights of both labeled and unlabeled samples as the low-rank representation (LRR) coefficients, has shown excellent performance in semi-supervised learning. In this paper, we additionally impose twofold constraints (local affinity and distant repulsion) on the LRR graph. The improved model, termed structure preserving LRR (SPLRR), can preserve the local geometrical structure but without distorting the distant repulsion property. Experiments are taken on three widely used face data sets to investigate the performance of SPLRR and the results show that it is superior to some state-of-the-art semi-supervised graphs. © Springer-Verlag 2013.

关键词： Face recognition

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An unsupervised aspect detection model for sentiment analysis of reviews

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18th International Conference on Application of Natural Language to Information Systems, NLDB 2013

作者： Bagheri, Ayoub Saraee, Mohamad De Jong, Franciska Intelligent Database Data Mining and Bioinformatics Lab Electrical and Computer Engineering Department Isfahan University of Technology Isfahan Iran School of Computing Science and Engineering University of Salford Manchester United Kingdom Human Media Interaction University of Twente P.O. Box 217 7500 AE Enschede Netherlands

ISBN: (纸本)9783642388231

With the rapid growth of user-generated content on the internet, sentiment analysis of online reviews has become a hot research topic recently, but due to variety and wide range of products and services, the supervised and domain-specific models are often not practical. As the number of reviews expands, it is essential to develop an efficient sentiment analysis model that is capable of extracting product aspects and determining the sentiments for aspects. In this paper, we propose an unsupervised model for detecting aspects in reviews. In this model, first a generalized method is proposed to learn multi-word aspects. Second, a set of heuristic rules is employed to take into account the influence of an opinion word on detecting the aspect. Third a new metric based on mutual information and aspect frequency is proposed to score aspects with a new bootstrapping iterative algorithm. The presented bootstrapping algorithm works with an unsupervised seed set. Finally two pruning methods based on the relations between aspects in reviews are presented to remove incorrect aspects. The proposed model does not require labeled training data and can be applicable to other languages or domains. We demonstrate the effectiveness of our model on a collection of product reviews dataset, where it outperforms other techniques. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Sentiment analysis

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Performance Pattern of Unified Parallel C on Multi-Core Clusters

Performance Pattern of Unified Parallel C on Multi-Core Clus...

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International Workshop on Intelligent Communication and Social Networks

作者： Nor Asilah Wati Abdul Hamid Olivier Serres Ahmad Anbar Sazlinah Hassan High Performance Computing Lab (HPCL) Department of Electrical and Computer Engineering The George Washington University Faculty of Computer Science & Information Technology Universiti Putra Malaysia

ISBN: (纸本)9781479909735

The Partitioned Global Address Space (PGAS) model has been widely used in multi-core clusters as an alternative to MPI. Among the widespread use is Unified Parallel C (UPC). Previous research has shown that UPC performance is comparable with MPI, however in certain cases UPC require hand-tuning techniques such as pre-fetching and privatized pointers-to-shared to improve the performance. In this paper we reviews, evaluate and analyze the performance pattern between UPC Naive, UPC optimize and MPI on two different multi-core clusters architecture. We focus our study using matrix multiplication as the benchmark and perform our experimental on two distributed memory machine;Cray XE6 with Gemini interconnects and Sun Cluster with Infiniband interconnects. We provide analysis on each core execution time to understand the pattern of communication for both machines. We also demonstrate the gaps between naive and optimized are depends on the compiler with its associate distributed memory machine. We also observed unnecessary optimization for certain programs related to HPC architecture and compiler.

关键词： Performance Evaluation PGAS UPC MPI Gemini

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Decentralized Output Synchronization of Heterogeneous Linear Systems with Fixed and Switching Topology via Self-Triggered Communication

Decentralized Output Synchronization of Heterogeneous Linear...

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American Control Conference

作者： Domagoj Tolic Rafael Fierro Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia MARHES Lab Department of Electrical and Computer Engineering University of New Mexico Albuquerque New Mexico 87131-0001 USA

ISBN: (纸本)9781479901777

In this paper, we investigate a decentralized output synchronization problem of heterogeneous linear systems. Motivated by recent results in the literature, we develop a self-triggered output broadcasting policy for the interconnected systems. In other words, each system broadcasts its outputs only when necessary in order to achieve output synchronization. Consequently, the control signal of each system is updated based on currently available (but outdated) information received from the neighbors. These broadcasting time instants adapt to the current communication topology. For a fixed topology, our broadcasting policy yields global exponential output synchronization, and L_p-stable output synchronization in the presence of disturbances. Employing a converse Lyapunov theorem for impulsive systems, we provide an average dwell-time condition that yields disturbance-to-state stable output synchronization in case of switching topology. The proposed approach is applicable to directed and unbalanced communication topologies. Finally, our results are corroborated by numerical simulations.

关键词： literature interconnected interconnected systems

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A comprehensive QoS determination model for Infrastructure-as-a-Service clouds

A comprehensive QoS determination model for Infrastructure-a...

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2013 IEEE International Conference on Automation Science and engineering, CASE 2013

作者： Xia, Yunni Zhou, Mengchu Luo, Xin Zhu, Qingsheng Software Theory and Technology Chongqing Key Lab Chongqing University Chongqing 400030 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States

ISBN: (纸本)9781479915156

Cloud computing is a recently developed new technology for complex systems with massive service sharing, which is different from the resource sharing of the grid computing systems. In a cloud environment, service requests from users go through numerous provider specific steps from the instant it is submitted to when the service is fully delivered. Quality modeling and analysis of clouds are not easy tasks because of the complexity of the provisioning mechanism and the dynamic cloud environment. This study proposes an analytical modelbased approach for quality evaluation of Infrastructure-as-a-Service cloud and consider expected request completion time, rejection probability, and system overhead rate as key QoS metrics. It also features with the modeling of different warming and cooling strategies of machines and the ability to identify the optimal balance between system overhead and performance. © 2013 IEEE.

关键词： Quality control

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Leveraging Performance Counters and Execution Logs to Diagnose Memory-Related Performance Issues

Leveraging Performance Counters and Execution Logs to Diagno...

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International Conference on Software Maintenance (ICSM)

作者： Mark D. Syer Zhen Ming Jiang Meiyappan Nagappan Ahmed E. Hassan Mohamed Nasser Parminder Flora Software Analysis and Intelligence Lab Queen's University Canada Department of Electrical Engineering & Computer Science York University Canada Performance Engineering School of Computing BlackBerry Canada

Load tests ensure that software systems are able to perform under the expected workloads. The current state of load test analysis requires significant manual review of performance counters and execution logs, and a high degree of system-specific expertise. In particular, memory-related issues (e.g., memory leaks or spikes), which may degrade performance and cause crashes, are difficult to diagnose. Performance analysts must correlate hundreds of megabytes or gigabytes of performance counters (to understand resource usage) with execution logs (to understand system behaviour). However, little work has been done to combine these two types of information to assist performance analysts in their diagnosis. We propose an automated approach that combines performance counters and execution logs to diagnose memory-related issues in load tests. We perform three case studies on two systems: one open-source system and one large-scale enterprise system. Our approach flags ≤ 0.1% of the execution logs with a precision ≥ 80%.

关键词： Radiation detectors Standards Transient analysis Lifting equipment Memory management Couplings Visualization

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Grand challenges in modeling and simulation: Expanding our horizons 13

Grand challenges in modeling and simulation: Expanding our h...

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2013 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, SIGSIM-PADS 2013

作者： Taylor, Simon J.E. Balci, Osman Cai, Wentong Loper, Margaret L. Nicol, David M. Riley, George ICT Innovation Group Department of Information Systems and Computing Brunel University Uxbridge United Kingdom Department of Computer Science Virginia Tech. Blacksburg VA United States School of Computer Engineering Nanyang Technological University Singapore Singapore Information and Communications Lab. Georgia Tech. Research Institute Atlanta GA United States Information Trust Institute University of Illinois at Urbana-Champaign Urbana-Champaign IL United States School of Electrical and Computer Engineering Georgia Tech. Atlanta GA United States

ISBN: (纸本)9781450319201

There continues to be many advances in the theory and practice of Modeling and Simulation (M&S). However, some of these can be considered as Grand Challenges;issues whose solutions require significant focused effort across a community, sometimes with ground-breaking collaborations with new disciplines. In 2002, the first M&S Grand Challenges Workshop was held in Dagstuhl, Germany, in an attempt to focus efforts on key areas. In 2012, a new initiative was launched to continue these Grand Challenge efforts. Panel members of this third Grand Challenge present their views on M&S Grand Challenges. Themes presented in this panel include M&S Methodology;Agent-based M M&S in Systems engineering;Cyber Systems Modeling;and Network Simulation. © 2013 ACM.

关键词： Life cycle

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