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Protein-coding genes combined with long noncoding RNA as a novel transcriptome molecular staging model to predict the survival of patients with esophageal squamous cell carcinoma

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Cancer Communications 2018年第1期38卷 50-62页

作者： Jin-Cheng Guo Yang Wu Yang Chen Feng Pan Zhi-Yong Wu Jia-Sheng Zhang Jian-Yi Wu Xiu-E Xu Jian-Mei Zhao En-Min Li Yi Zhao Li-Yan Xu Key Laboratory of Molecular Biology in High Cancer Incidence Coastal Chaoshan Area of Guangdong Higher Education Institutes Shantou University Medical CollegeShantouGuangdong 515041P.R.China Department of Biochemistry and Molecular Biology Shantou University Medical CollegeShantouGuangdong 515041P.R.China Departments of Oncology Surgery Shantou Central HospitalAffiliated Shantou Hospital of Sun Yat-Sen UniversityShantouGuangdong 515041P.R.China Institute of Oncologic Pathology Shantou University Medical CollegeShantouGuangdong 515041P.R.China Key Laboratory of Intelligent Information Processing Advanced Computer Research CenterState Key Laboratory of Computer ArchitectureInstitute of Computing TechnologyChinese Academy of SciencesBeijing 100190P.R.China

Background:Esophageal squamous cell carcinoma(ESCC)is the predominant subtype of esophageal carcinoma in *** study was to develop a staging model to predict outcomes of patients with ***:Using Cox regression analysis,principal component analysis(PCA),partitioning clustering,Kaplan-Meier analysis,receiver operating characteristic(ROC)curve analysis,and classification and regression tree(CART)analysis,we mined the Gene Expression Omnibus database to determine the expression profiles of genes in 179 patients with ESCC from GSE63624 and GSE63622 ***:Univariate cox regression analysis of the GSE63624 dataset revealed that 2404 protein-coding genes(PCGs)and 635 long non-coding RNAs(lncRNAs)were associated with the survival of patients with *** categorized these PCGs and lncRNAs into three principal components(PCs),which were used to cluster the patients into three *** analysis demonstrated that the predictive ability of PCG-lncRNA PCs when applied to new patients was better than that of the tumor-node-metastasis staging(area under ROC curve[AUC]:0.69 vs.0.65,P<0.05).Accord-ingly,we constructed a molecular disaggregated model comprising one lncRNA and two PCGs,which we desig-nated as the LSB staging model using CART analysis in the GSE63624 *** LSB staging model classified the GSE63622 dataset of patients into three different groups,and its effectiveness was validated by analysis of another cohort of 105 ***:The LSB staging model has clinical significance for the prognosis prediction of patients with ESCC and may serve as a three-gene staging microarray.

关键词： Long non-coding RNA Protein-coding gene Esophageal squamous cell carcinoma Overall survival Staging model Transcriptome

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Simulation platform for X-Ray computed tomography based on low-power systems 15th

Simulation platform for X-Ray computed tomography based on l...

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15th International Conference on Algorithms and architectures for Parallel Processing, ICA3PP 2015

作者： Serrano, Estefania Blas, Javier Garcia Verza, Alberto Carretero, Jesus Computer Architecture and Technology Area Universidad Carlos III Madrid28911 Spain

ISBN: (纸本)9783319271392

Reconstruction of Computed Tomography (CT) images is a computationally and memory demanding tool. The creation of new algorithms for the reduction of the X-Ray dose and the increasing res- olution of the detectors have complicated the obtaining of a good performance. Accelerators have become essential for the processing of the algorithm in a reasonable time. Nowadays, with the emergence of new mobile architectures that are not only powerful but also energy efficient and the possibility of easily porting the already existing code thanks to different programming models they could become an alternative to desktop and high performance accelerators. We evaluate four different platforms for our simulation framework for CT images. The evaluation results demonstrate that although in terms of performance, low-power platforms are still far from GPGPUs, the reduction of the energy consumption to almost a half in the case of the Jetson TK1 is an evident incentive that can lead to the creation of smaller and mobile medical image scanners. © Springer International Publishing Switzerland 2015.

关键词： Energy utilization

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Using a sequential covering strategy for discovering fuzzy rules incrementally

Using a sequential covering strategy for discovering fuzzy r...

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IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015

作者： Garcia, David Gamez, Juan Carlos Gonzalez, Antonio Perez, Raul Departament of Computer Science and Artificial Intelligence ETSIIT University of Granada Granada Spain Departament of Computer Architecture and Technology Area University of Córdoba Córdoba Spain

ISBN: (纸本)9781467374286

The sequential covering strategy has been and still is a very common way to develop rule learning algorithms. This strategy follows a greedy procedure to learn rules, where, after each step one rule is obtained. Recently, we proposed a new sequential covering strategy that allowed the review of previously learned knowledge during the learning process itself. This review of knowledge allowed the algorithm to adapt to changes that may occur in the context of learning. Specifically, in this paper we consider the changes produced by the addition of new training examples, and therefore we make a proposal of incremental learning of fuzzy rules. We have performed several experiments to test the behavior of the proposal and the results have been very promising. © 2015 IEEE.

关键词： Fuzzy rules

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Using a sequential covering strategy for discovering fuzzy rules incrementally

Using a sequential covering strategy for discovering fuzzy r...

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IEEE International Conference on Fuzzy Systems

作者： David García Juan Carlos Gámez Antonio González Raúl Pérez Departament of Computer Science and Artificial Intelligence ETSIIT University of Granada Granada Spain Departament of Computer Architecture and Technology Area University of Cordoba Cordoba Spain

ISBN: (纸本)9781467374293

关键词： Genetic Fuzzy Systems Sequential Covering Incremental Learning Classification

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Mobiscool: 1st workshop on mobile, social and culturally oriented learning 15

Mobiscool: 1st workshop on mobile, social and culturally ori...

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17th International Conference on Human-computer Interaction with Mobile Devices and Services, MobileHCI 2015

作者： Nanavati, A.A. Rajput, N. Turunen, M. Knoche, H. Rehm, M. IBM Research India 4th Block-C Institutional Area Vasant Kunj New Delhi India Dept. of Computer Science University of Tampere Tampere Finland Department of Architecture Design and Media Technology Centre for Mobility and Urban Studies Aalborg University Denmark

ISBN: (纸本)9781450336536

There are two simultaneous transformative changes occuring in Education: the use of mobile and tablet devices for accessing educational content, and the rise of the MOOCs. Happening independently and in parallel are significant advances in interaction technologies through smartphones and tablets, and the rise in the use of social-media and social-network analytics in several domains. Given the extent of personal context that is available on the mobile device, how can the education experience be personalised, made social, and tailored to the cultural context of the learner? The goal of this proposal is twofold: (a) To understand the usage, and student behaviour in this new environment (MOOCS and mobile devices) and (b) To design experiments and implement them to make these new tools more effective by tailoring them to the individual student's personal, social and cultural settings and preferences.

关键词： Augmented reality

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1

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BMC Neurosci 2017年第SUPPL 1期18卷 58-58页

作者： Sue Denham Panayiota Poirazi Erik De Schutter Karl Friston Ho Ka Chan Thomas Nowotny Dongqi Han Sungho Hong Sophie Rosay Tanja Wernle Alessandro Treves Sarah Goethals Romain Brette Tomas Van Pottelbergh Rodolphe Sepulchre Alex D. Bird Hermann Cuntz Pedro J. Gonçalves Jan-Matthis Lueckmann Giacomo Bassetto Marcel Nonnenmacher Jakob H. Macke Audrey J. Sederberg Jason N. MacLean Stephanie E. Palmer Ulisse Ferrari Christophe Gardella Olivier Marre Thierry Mora Emina Ibrahimovic Martin Müller Jean-Pascal Pfister Tushar Chauhan Timothée Masquelier Alexandre Montlibert Benoit R. Cottereau Moritz Helias Jannis Schuecker David Dahmen Sven Goedeke Alexandre Hyafil Ainhoa Hermoso-Mendizabal Pavel E. Rueda-Orozco Santiago Jaramillo David Robbe Jaime de la Rocha Marie Rooy Fani Koukouli David DiGregorio Uwe Maskos Boris Gutkin Andrey Yu Verisokin Darya V. Verveyko Dmitry E. Postnov Willy Wong Omid Talakoub Robert Chen Milos Popovic Dmitriy Lisitsyn Eric Drebitz Iris Grothe Sunita Mandon Andreas Kreiter Udo Ernst Peter A. Robinson Xuelong Zhao Kevin M. Aquino John D. Griffiths Grishma Mehta-Pandejee Natasha Gabay James MacLaurin Somwrita Sarkar Tim Kunze Jens Haueisen Thomas R. Knösche Subutai Ahmad Yuwei Cui Marcus Lewis Jeff Hawkins Simona Olmi Spase Petkoski Fabrice Bartolomei Maxime Guye Viktor Jirsa Hazem Toutounji Daniel Durstewitz Matteo Cantarelli Adrian Quintana Boris Marin Matt Earnshaw Padraig Gleeson Robert Court Robert McDougal R. Angus Silver Salvador Dura-Bernal Stephen Larson William W. Lytton Giovanni Idili Lorenzo Posani Simona Cocco Karel Ježek Rémi Monasson School of Psychology Faculty of Health & Human Sciences Plymouth University Plymouth Devon PL4 8AA UK Institute of Molecular Biology and Biotechnology (IMBB) Foundation for Research and Technology-Hellas (FORTH) Heraklion Crete Greece Okinawa Institute of Science and Technology Graduate University Okinawa Japan Wellcome Trust Centre for Neuroimaging Institute of Neurology UCL London WC1N 3BG UK School of Engineering and Informatics University of Sussex Brighton BN1 9QJ UK Graduate School Okinawa Institute of Science and Technology Okinawa 904-0495 Japan Computational Neuroscience Unit Okinawa Institute of Science and Technology Okinawa 904-0495 Japan Cognitive Neuroscience Area Scuola Internazionale Superiore di Studi Avanzati Trieste 34136 Italy Kavli Institute for Systems Neuroscience NTNU Trondheim 7030 Norway Institut de la Vision Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Paris 75012 France Department of Engineering University of Cambridge Cambridge Cambridgeshire CB2 1PZ UK Ernst Strüngmann Institute for Neuroscience Max Planck Society Frankfurt Germany Frankfurt Institute for Advanced Studies Frankfurt Germany Neural Systems Analysis Research Center Caesar An Associate of the Max Planck Society Bonn Germany Max Planck Institute for Biological Cybernetics Tübingen Germany Bernstein Center for Computational Neuroscience Tübingen Germany Present Address: Biomedical Engineering Department Georgia Institute of Technology Atlanta GA 30306 USA Department of Neurobiology University of Chicago Chicago IL 60637 USA Department of Organismal Biology and Anatomy University of Chicago Chicago IL 60637 USA Committee on Computational Neuroscience University of Chicago Chicago IL 60637 USA Institut de la Vision Sorbonne Universités INSERM Paris France Laboratoire de Physique Statistique Ecole Normale Supérieure Paris France Institute of Molecular Life Sciences University of Zürich 8057 Zürich Switzerland Institute of Neuroinformatics Univer

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VIDAS: Object-based virtualized data sharing for high performance storage I/O

VIDAS: Object-based virtualized data sharing for high perfor...

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4th ACM Workshop on Scientific Cloud Computing, ScienceCloud 2013

作者： Llopis, Pablo Blas, Javier Isaila, Florin Carretero, Jesus Computer Architecture and Technology Area Universidad Carlos III de Madrid Madrid Spain

ISBN: (纸本)9781450319799

With scientific computing in the cloud gaining popularity and using every time larger data sets, high performance storage I/O in virtualized environments is substantially increasing in importance. However, exploiting the performance potential of the storage I/O on today's virtualized architectures is complex, due to the limitations of POSIX standard for storage I/O and the lack of integration of related mechanisms such as data sharing, storage I/O coordination, relaxing the consistency semantics, and data locality awareness. In this paper we propose VIDAS (Virtualized DAta Sharing), an object-based virtualized data store that targets to integrate the above mechanisms through a simple and powerful interface. VIDAS can be used to efficiently and consistently share access to externally stored data in virtualized environments based on a shared pool of storage objects. We show how VIDAS can be used for straightforwardly implementing I/O coordination and data sharing for two common high-performance patterns: inter-domain write-reader and inter-domain collective I/O. We present the implementation and evaluation of VIDAS for the Xen virtualization solution. In addition, we present a novel mechanism for efficiently sharing memory among an arbitrary number of virtual machines. © 2013 ACM.

关键词： Virtualization

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A comparative study and evaluation of parallel programming models for shared-memory parallel architectures

A comparative study and evaluation of parallel programming m...

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作者： Sanchez, Luis Miguel Fernandez, Javier Sotomayor, Rafael Escolar, Soledad Garcia, J. Daniel. Computer Architecture and Technology Area Universidad Carlos III de Madrid Madrid Colmenarejo 28270 Spain

Nowadays, shared-memory parallel architectures have evolved and new programming frameworks have appeared that exploit these architectures: OpenMP, TBB, Cilk Plus, ArBB and OpenCL. This article focuses on the most extended of these frameworks in commercial and scientific areas. This paper shows a comparative study of these frameworks and an evaluation. The study covers several capacities, such as task deployment, scheduling techniques, or programming language abstractions. The evaluation measures three dimensions: code development complexity, performance and efficiency, measure as speedup per watt. For this evaluation, several parallel benchmarks have been implemented with each framework. These benchmarks are created to cover certain scenarios, like regular memory access or irregular computation. The conclusions show some highlights, like the fact that some frameworks (OpenMP, Cilk Plus) are better for transforming quickly a sequential code, others (TBB) have a small footprint which is ideal for small problems, and others (OpenCL) are suited for heterogeneous architectures but they require a very complex development process. The conclusions also show that the vectorization support is more critical than multitasking to achieve efficiency for those problems where this approach fits. © 2013 Ohmsha and Springer Japan.

关键词： Electric power utilization

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Enhancing file transfer scheduling and server utilization in data distribution infrastructures

Enhancing file transfer scheduling and server utilization in...

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2012 IEEE 20th International Symposium on Modeling, Analysis and Simulation of computer and Telecommunication Systems, MASCOTS 2012

作者： Higuero, Daniel Tirado, Juan M. Isaila, Florin Carretero, Jesús Computer Architecture and Technology Area Universidad Carlos III de Madrid Madrid Spain

ISBN: (纸本)9780769547930

This paper presents a methodology for efficiently solving the file transfer scheduling problem in a distributed environment. Our solution is based on the relaxation of an objective-based time-indexed formulation of a linear programming problem. The main contributions of this paper are the following. First, we introduce a novel approach to the relaxation of the time-indexed formulation of the transfer scheduling problem in multi-server and multi-user environments. Our solution consists of reducing the complexity of the optimization by transforming it into an approximation problem, whose proximity to the optimal solution can be controlled depending on practical and computational needs. Second, we present a distributed deployment of our methodology, which leverages the inherent parallelism of the divide-and-conquer approach in order to speed-up the solving process. Third, we demonstrate that our methodology is able to considerably reduce the schedule length and idle time in a computationally tractable way. © 2012 IEEE.

关键词： Scheduling

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A comparative evaluation of parallel programming models for shared-memory architectures

A comparative evaluation of parallel programming models for ...

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2012 10th IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2012

作者： Sanchez, Luis Miguel Fernandez, Javier Sotomayor, Rafael Garcia, J. Daniel Computer Architecture and Technology Area Computer Science Department Universidad Carlos III De Madrid Madrid Colmenarejo 28270 Spain

ISBN: (纸本)9780769547015

Nowadays, most computers that are commercially available off-the-shelf (COTS) include hardware features that increase the performance of parallel general-purpose threads (hyper threading, multicore, ccNUMA architectures) or SIMD kernels (CPU vector instructions, GPUs). The purpose of this paper is to perform a compared evaluation of several parallel programming models where each one is fitted to exploit some of these features but also each one requires a different level of programming skills. Four parallel programming models (OpenMP, Intel TBB, Intel ArBB, and CUDA) have been selected. The idea is to cover a wide spectrum of programming models and most of the parallel hardware features included in modern computers. On one hand, OpenMP and TBB platforms, that exploit parallel threads running on multicore systems. On the other hand, ArBB, that combines muticore parallel threads and multicore SIMD features with a simpler programming model, and CUDA that exploits SIMD features of the GPU hardware. Our results obtained with the benchmarks used on this paper suggest that OpenMP and TBB have a lower performance compared to ArBB and CUDA. But also that ArBB performance tends to be comparable with CUDA performance in most cases (although it is normally lower). Thus, there are evidences that a careful designed top range multicore and multisocket architecture, can be comparable in terms of performance with top range GPU cards for many applications, with the advantage of a simpler programming model. © 2012 IEEE.

关键词： Parallel programming

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