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Application of Graph Theory to Evaluate Chemical Reactions in Cells

Journal of Physics: Conference Series 2019年第1期1391卷

作者： Sachiyo Aburatani Yuichi Kokabu Ryota Teshima Teppei Ogawa Michihiro Araki Tomokazu Shiarai Computational Bio Big Data Open Innovation Lab. (CBBD-OIL) National Institute of Advanced Industrial Science and Technology (AIST) AIST Tokyo Waterfront Main Bldg. 2-3-26 Aomi Koto-ku Tokyo 135-0064 Japan Bioscience Department Mitsui Knowledge Industry Co. Ltd. Atago Green Hills MORI Tower 2-5-1 Atago Minato-ku Tokyo 105-6215 Japan Graduate School of Medicine Kyoto University 54 Kawahara-cho Shogoin Sakyo-ku Kyoto 606-8507 Japan Center for Sustainable Resource Science RIKEN 1-7-22 Suehiro-cho Tsurumi-ku Yokohama Kanagawa 230-0045 Japan

Chemical reactions occur in cells for survival and adaptation to various conditions. After these chemical reactions, the reactants and products are often sequentially modified through metabolic pathways. In this study, we defined new features to evaluate the possibility of such inferred metabolic pathways. We focused on the main chain structure of a compound as a non-directional graph, and developed a method to define the similarity between these main chain structure graphs. In this study, we defined four features: 1) the number of main chain graph nodes, 2) the graphical density of the main chain graph, 3) the chemical density of the main chain, and 4) the graph centrality of the reaction group in the main chain graph. We defined the main chain structures of about 16,000 chemical compounds, and calculated the values of the four features by the defined equations for each compound. Finally, we calculated the correlation coefficients between all chemical compound pairs from the four defined features. A comparison of the similarities of the main chain graphs between known chemical reactions revealed that our defined features are suitable for detecting the possible reactions.

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Semantic mapping: Towards contextual and trend analysis of behaviours and practices

Semantic mapping: Towards contextual and trend analysis of b...

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2016 Working Notes of Conference and labs of the Evaluation Forum, CLEF 2016

作者： Murtagh, Fionn Big Data Lab Department of Computer Science and Mathematics University of Derby DerbyDE22 1GB United Kingdom Department of Computing Goldsmiths University of London LondonSW14 6NW United Kingdom

As a platform for unsupervised data mining and pattern recognition, we use Correspondence Analysis on Twitter content from May to December 2015. The following data characteristics are well addressed: exponentially distributed data properties, and major imbalance between categories. Contextualization is supported. To both focus on informative resolution scale in one's data, and to handle large data sets, the granularity of point clouds offers benefits.

关键词： data mining

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Overview of the CL-SciSumm 2016 Shared Task

Overview of the CL-SciSumm 2016 Shared Task

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Joint Workshop on Bibliometric-Enhanced Information Retrieval and Natural Language Processing for Digital Libraries, BIRNDL 2016

作者： Jaidka, Kokil Chandrasekaran, Muthu Kumar Rustagi, Sajal Kan, Min-Yen Big Data Experience Lab Adobe Research India India School of Computing National University of Singapore Singapore Singapore Dept. of Computer Science and Engineering Indian Institute of Technology Roorkee India Interactive and Digital Media Institute National University of Singapore Singapore Singapore

The CL-SciSumm 2016 Shared Task is the first medium-scale shared task on scientific document summarization in the computational linguistics (CL) domain. The task built off of the experience and training data set created in its namesake pilot task, which was conducted in 2014 by the same organizing committee. The track included three tasks involving: (1A) identifying relationships between citing documents and the referred document, (1B) classifying the discourse facets, and (2) generating the abstractive summary. The dataset comprised 30 annotated sets of citing and reference papers from the open access research papers in the CL domain. This overview paper describes the participation and the official results of the second CL-SciSumm Shared Task, organized as a part of the Joint Workshop onBibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2016), held in New Jersey,USA in June, 2016. The annotated dataset used for this shared task and the scripts used for evaluation can be accessed and used by the community at: https://***/WING-NUS/scisumm-corpus.

关键词： Digital libraries

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Piggyback game: Efficient event stream dissemination in Online Social Network systems

Piggyback game: Efficient event stream dissemination in Onli...

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International Conference on Network Protocols

作者： Fan Zhang Hanhua Chen Hai Jin Services Computing Technology and System Lab Big Data Technology and System Lab and Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781509032822

Event stream dissemination dominates the workloads in large-scale Online Social Network (OSN) systems. Based on the de facto per-user view data storage, event stream dissemination raises a large amount of inter-server traffics due to the complex interconnection among OSN users. The state-of-the-art schemes mainly explore the structure features of social graphs to reduce the inter-server messages for event stream dissemination. Different sub-graph structures are exploited for achieving the approximated optimal assignment. However, such schemes incur high costs of computation or communication. In this work, we follow a different design philosophy by using a game theoretic approach, which decomposes the high complex graph computation problem into individuals' rational strategy selection of each node. Specifically, we propose a novel social piggyback game to achieve a more efficient solution. We mathematically prove the existing of the Nash Equilibrium of the social piggyback game. Moreover, we propose an efficient best response dynamic algorithm to achieve the Nash Equilibrium, which quickly converges in a small number of iterations for large-scale OSNs. We further show that the communication cost of this design achieves a 1.5-approximation of the theoretical social optimal. We conduct comprehensive experiments to evaluate the performance of this design using large-scale real-world traces from popular OSN systems. Results show that the social piggyback game achieves a significant 302× improvement in system efficiency compared to existing schemes.

关键词： Games Schedules Heuristic algorithms Algorithm design and analysis Nash equilibrium Social network services Servers

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Software Defined Networking Based On-Demand Routing Protocol in Vehicle Ad Hoc Networks

Software Defined Networking Based On-Demand Routing Protocol...

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International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Baihong Dong Weigang Wu Zhiwei Yang Junjie Li School of Data and Computer Science Sun Yat-Sen University Guangdong Key Lab. of Big Data Analysis and Processing Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Guangzhou

ISBN: (纸本)9781509056972

This paper comes up with a SDN based On-Demand Routing Protocol, SVAO, which separates data forwarding layer and network control layer, as in SDN, to enhance the data transmission efficiency within VANETs. The Roadside Service Unit plays the role of Local Controller and is in charge of selecting vehicles to forward packet within a road segment. All the vehicles state in the road. Correspondingly, a two-level design is used. Global Level is distributed and adopts a ranked query scheme to collect vehicle information and determine the road segments along which a message should be forwarded. And the Local Level is in charge of selecting forwarding vehicles in each road segment determined by the global level. We compare SVAO with popular ad-hoc network routing protocols, including OLSR, DSR, DSDV, and DB via simulations. We consider the impact of vehicle density, speed on data transmission rate and average packet delay. The simulation results show that in case of large network scales or high vehicle speed, SVAO performs better than the others.

关键词： Routing protocols Roads Routing Ad hoc networks Topology Vehicle dynamics

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Robust frequent directions with application in online learning

arXiv

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arXiv 2017年

作者： Luo, Luo Chen, Cheng Zhang, Zhihua Li, Wu-Jun Zhang, Tong Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China National Engineering Lab for Big Data Analysis and Applications School of Mathematical Sciences Peking University 5 Yiheyuan Road Beijing100871 China National Key Laboratory for Novel Software Technology Collaborative Innovation Center of Novel Software Technology and Industrialization Department of Computer Science and Technology Nanjing University 163 Xianlin Avenue Nanjing210023 China Computer Science & Mathematics Hong Kong University of Science and Technology Hong Kong

The frequent directions (FD) technique is a deterministic approach for online sketching that has many applications in machine learning. The conventional FD is a heuristic procedure that often outputs rank deficient matrices. To overcome the rank deficiency problem, we propose a new sketching strategy called robust frequent directions (RFD) by introducing a regularization term. RFD can be derived from an optimization problem. It updates the sketch matrix and the regularization term adaptively and jointly. RFD reduces the approximation error of FD without increasing the computational cost. We also apply RFD to online learning and propose an effective hyperparameter-free online Newton algorithm. We derive a regret bound for our online Newton algorithm based on RFD, which guarantees the robustness of the algorithm. The experimental studies demonstrate that the proposed method outperforms state-of-the-art second order online learning algorithms. Copyright © 2017, The Authors. All rights reserved.

关键词： Heuristic methods

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Analyzing information sharing strategies of users in online social networks

Analyzing information sharing strategies of users in online ...

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2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016

作者： Nguyen, Dong-Anh Tan, Shulong Ramanathan, Ram Yan, Xifeng Department of Computer Science University of California Santa BarbaraCA93106 United States Baidu Big Data Lab. 1195 Bordeaux Drive SunnyvaleCA94089 United States Network Research Department Raytheon BBN Technologies 10 Moulton Street CambridgeMA02138 United States

ISBN: (纸本)9781509028467

User information sharing is an important behavior in online social networks. Understanding such behavior could help in various applications such as user modeling, information cascade analysis, viral marketing, etc. In this paper, we aim to understand the strategies users employ to make retweet decision. We are interested in investigating whether these strategies in online social network contain significant information about users and can be used to further characterize users. We propose a flexible model that captures a number of behavior signals affecting user's retweet decision. Our empirical results show that the inferred strategies can help increase the performance of retweet prediction. © 2016 IEEE.

关键词： Social networking (online)

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PO-329 Rejecting neutral tumour evolution across human cancer types

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ESMO Open 2018年 3卷 A357-A357页

作者： Tarabichi, M. Martincorena, I. Gerstung, M. Markowetz, F. Spellman, P. Morris, Q. Lingjærde, O.C. Wedge, D. Loo, P. Van Pcawg, W.G. The Francis Crick Institute Cancer Genomics London UK The Wellcome Trust Sanger Institute Inigo Martincorena lab Cambridge UK European Bioinformatics Institute EMBL – EBI- Wellcome Genome Campus Moritz Gerstung lab Cambridge UK CRUK Cancer Institute Markowetz lab Cambridge UK Oregon Health and Science University Spellman lab Portland USA Donnelly Centre for Cellular and Biomolecular Research- University of Toronto Morris lab Toronto Canada Centre for Computational Inference in Evolutionary Life Science- University of Oslo Department of statistics Oslo Norway Oxford Big Data Institute Wedge lab Oxford UK PCAWG PCAWG – working group 11 London UK

ABSTRACTIntroductionClusters of subclonal mutations attributed to subclonal expansions have been observed across most cancer types. To date it is not clear what fraction of these expansions can be ascribed to selective sweeps or genetic drifts. The widely held theory states that tumour expansion arises from a series of selective sweeps. However, Williams et al. (Nat. Genet. 48:238–224, 2016) recently claimed to have identified neutral tumour evolution in one third of 904 samples from The Cancer Genome Atlas (TCGA). Material and methodsFirst, using the same equations we simulated data of tumour undergoing selective sweeps. Second, we simulated data using branching processes, i.e. more realistic models. Third, we analysed the mutations from ~1600 exomes and ~1500 whole genomes of real tumours from TCGA and the International Cancer Genome Consortium, respectively. We grouped them into neutral and non-neutral tumours according to the rationale described by Williams et al. We then applied dN/dS, an orthogonal widely used approach to detect selection in non-synonymous mutations of coding regions. Finally, we ran dN/dS on subclonal mutations within individual cancer types. Results and discussionsApplication of the method described by Williams et al. led to over-calling of neutrality and led to random predictions (area under the curve~=50%) in simulations based on the deterministic or stochastic models, respectively. dN/dS analyses revealed significant and widespread positive selection in clonal and subclonal mutations within both neutral and non-neutral groups. Despite power limits, the subclonal mutations of many individual cancer types displayed dN/dS>1, evidence for positive selection. ConclusionAltogether, our results point to the lack of evidence for neutral tumour evolution and uncovered strong positive selection within subclonal mutations across cancers.

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A novel reversible watermarking scheme for relational databases protection based on histogram shifting

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Journal of Information Hiding and Multimedia Signal Processing 2016年第2期7卷 266-276页

作者： Ma, Yu-Jia Zhu, Yue-Sheng Liu, Xi-Yao Communication and Information Security Lab Institute of Big Data Technologies Shenzhen Graduate School Peking University Shenzhen China School of Information Science and Engineering Central South University Changsha China

The watermarking technique can be used to protect the ownership of relational databases by hiding some ownership information into the relational databases. In this paper, a novel robust reversible watermarking scheme for relational database protection is proposed to increase the embedding capacity by developing an improved histogram shifting with binary tree structure and an attribute selection scheme. The iteratively embedded watermarks are utilized by a majority voting mechanism to enhance the robustness of the proposed scheme. In addition, the attribute selection and cell selection are employed to reduce the distortion caused by the watermark embedding. The experimental results show that our proposed scheme can provide higher embedding capacity and stronger robustness with low distortion compared with other watermarking schemes for relational databases. © 2016.

关键词： Iterative methods

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Promoting Business Analytics and Quantitative Management of Technology: Preface for ITQM 2016

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Procedia Computer science 2016年 91卷 1-8页

作者： Lee, Heeseok Shi, Yong Lee, Jongwon Cordova, Felisa Dzitac, Ioan Kou, Gang Li, Jaiping College of Business Korea Advanced Institute Science and Technology Dongdaemum-gu Seoul130-722 Korea Republic of Research Center on Fictitiotus Economy and Data Science Key Lab of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China College of Information Science and Technology University of Nebraska at Omaha OmahaNE68182 United States School of Business Administration Hoseo University Asan-si Chungcheongnam-do336-795 Korea Republic of Faculty of Engineering and Business University Finis Terrae Pedro de Valdivia 1509. Providencia Santiago Chile Universitatea Agora Agora University Piata Tineretului 8 Oradea410526 Romania School of Business Administration Southwestern University of Finance and Economics Chengdu Sichuan61130 China Institute of Policy and Management Chinese Academy of Sciences Beijing100190 China

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