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IEEE International Conference on Data Mining Workshops, ICDM Workshops 2008

作者： Dutta, Haimonti Kargupta, Hillol Center for Computational Learning Systems Columbia University New York NY 10115 United States Department of Computer Science and Electrical Engineering University of Maryland Baltimore County United States

ISBN: (纸本)9780769535036

Advances in computing and communication has resulted in very large scale distributed environments in recent years. They are capable of storing large volumes of data and often have multiple compute nodes. However, the inherent heterogeneity of data components, the dynamic nature of distributed systems, the need for information synchronization and data fusion over a network and security and access control issues makes the problem of resource management and monitoring a tremendous challenge. In particular, centralized algorithms for management of resources and data may not be sufficient to manage complex distributed systems. In this paper, we present a distributed algorithm for resource and data management which builds on the traditional simplex algorithm used for solving linear optimization problems. Our distributed algorithm is an exact one meaning its results are identical if run in a centralized setting. We provide extensive analytical results and experiments on simulated data to demonstrate the performance of our algorithm. © 2008 IEEE.

关键词： Data fusion

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Clustering process and precipitation hardening in Fe-Cu alloys: First-principle and empirical model evaluations 4

Clustering process and precipitation hardening in Fe-Cu allo...

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4th International Conference on Multiscale Materials Modeling, MMM 2008

作者： Tsuru, Tomohito Suzuki, Chikashi Yamaguchi, Masatake Kaji, Yoshiyuki Nuclear Science and Engineering Directorate Japan Atomic Energy Agency 2-4 Shirakata-Shirane Tokai-mura Ibaraki319-1195 Japan Center for Computational Science and e-Systems Japan Atomic Energy Agency Japan

ISBN: (纸本)9780615247816

It is well known that the mechanical properties of reactor pressure vessel have changed due to ageing and neutron irradiation. Neutron irradiation enhances the nucleation of lattice defects such as the formation and growth of Cu precipitates. In the present study, the clustering process and interaction between precipitation and pure edge dislocation in Fe-Cu alloys are investigated. Fundamental physical properties associated with classical nucleation theory are first estimated by first-principle calculations based on the projector augmented wave method, and the diffusion processes of impurity ions in -Fe is comparatively evaluated by first-principle transition state analysis. The heat of solution and the activation energy for the migration of Cu is smaller than other ion species. It is found that these characteristic features are derived from the weak directional influence and low binding energy between valence electrons. On the other hand, a large number of atomistic simulations have been studied to investigate the self-interstitial atom and their clusters in -Fe under radiation damage environment. We perform a sequence of molecular dynamics simulations to investigate the interaction between a pure edge dislocation and spherical Cu precipitate. The hypothetical rigid body precipitations as well as Cu precipitates are considered for comparison of the characteristics of the precipitation types. Accordingly we can specify the size and spacing effects on the yield stress and the interaction mechanisms between precipitate and dislocation. © MMM 2008. All rights reserved.

关键词： Copper alloys

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The Broad Institute-Six Years Later

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CHEMISTRY & BIOLOGY 2010年第4期17卷 311-312页

作者： McCarthy, Alice Main Text “In June 2003 the scientific and medical communities at MIT Harvard University and its affiliated hospitals and the Whitehead Institute banded together as collaborating partners to form the Eli and Edythe L. Broad Institute based in Cambridge MA. The Broad Institute established with initial funding from a $100 million philanthropic donation from the Los Angeles-based Broad family was primarily viewed as a marriage between the Whitehead Institute's Center for Genome Research (WICGR) and the Harvard Institute of Chemistry and Cell Biology (ICCB). Eli Broad founder and chairman of AIG SunAmerica Inc. explained “the purpose of the Broad Institute is to create a new type of research institute to build on the accomplishments of the human genome project and to move to clinical applications to both prevent and cure diseases.” Every Thursday morning we meet with perhaps 20 faculty members and 100 other researchers to discuss what we're all doing and should be doing next. -David Altschuler This paragraph was written five years ago when the Broad Institute was in its very earliest days as a life science research community (McCarthy 2005). Since that time “the Broad” as it's known has kept true to Eli Broad's vision having attracted a talented group of researchers faculty trainees and professional staff. This 1600 person research community known internally as “Broadies” includes faculty staff and students from throughout the MIT and Harvard biomedical research communities and beyond with collaborations spanning over a hundred private and public institutions in more than 40 countries worldwide. “What is special about the Broad is that we have people from Harvard MIT and the Harvard hospitals come together and work on problems of shared interest that could not be solved in their own individuals labs” explains David Altshuler M.D. Ph.D. Deputy Director and one of the Broad's six core faculty members. “These problems require expertise beyond any one principal investigator and in

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6th Asia-Pacific Bioinformatics Conference, APBC 2008

作者： Li, Yuan-Peng Lu, Bao-Liang Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dong Chuan Road Shanghai 200240 China Laboratory for Computational Biology Shanghai Center for Systems Biomedicine 800 Dong Chuan Road Shanghai 200240 China

ISBN: (纸本)9781848161085

The similarity of two gene products can be used to solve many problems in information biology. Since one gene product corresponds to several GO (Gene Ontology) terms, one way to calculate the gene product similarity is to use the similarity of their GO terms. This GO term similarity can be defined as the semantic similarity on the GO graph. There are many kinds of similarity definitions of two GO terms, but the information of the GO graph is not used efficiently. This paper presents a new way to mine more information of the GO graph by regarding edge as information content and using the information of negation on the semantic graph. A simple experiment is conducted and, as a result, the accuracy increased by 8.3 percent in average, compared with the traditional method which uses node as information source.

关键词： Gene Ontology

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Classification of protein sequences based on word segmentation methods

Classification of protein sequences based on word segmentati...

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6th Asia-Pacific Bioinformatics Conference, APBC 2008

作者： Yang, Yang Lu, Bao-Liang Yang, Wen-Yun Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dong Chuan Road Shanghai 200240 China Laboratory for Computational Biology Shanghai Center for Systems Biomedicine 800 Dong Chuan Road Shanghai 200240 China

ISBN: (纸本)9781848161085

Protein sequences contain great potential revealing protein function, structure families and evolution information. Classifying protein sequences into different functional groups or families based on their sequence patterns has attracted lots of research efforts in the last decade. A key issue of these classification systems is how to interpret and represent protein sequences, which largely determines the performance of classifiers. Inspired by text classification and Chinese word segmentation techniques, we propose a segmentation-based feature extraction method. The extracted features include selected words, i.e., substrings of the sequences, and also motifs specified in public database. They are segmented out and their occurrence frequencies are recorded as the feature vector values. We conducted experiments on two protein data sets. One is a set of SCOP families, and the other is GPCR family. Experiments in classification of SCOP protein families show that the proposed method not only results in an extremely condensed feature set but also achieves higher accuracy than the methods based on whole k-spectrum feature space. And it also performs comparably to the most powerful classifiers for GPCR level I and level II subfamily recognition with 92.6 and 88.8% accuracy, respectively.

关键词： Classification (of information)

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OpenMPD: A Directive-Based Data Parallel Language Extension for Distributed Memory systems

OpenMPD: A Directive-Based Data Parallel Language Extension ...

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International Conference on Parallel processing Workshops (ICPPW)

作者： Jinpil Lee Mitsuhisa Sato Taisuke Boku Graduate School of Systems and Information Engineering University of Tsukuba Japan Center for Computational Science University of Tsukuba Japan

Open MPD is a language extension for programming on distributed memory systems that helps users by having minimal and simple notations. Although MPI is the de facto standard for parallel programming on distributed memory systems, writing MPI programs is often a time-consuming and complicated process. Open MPD supports typical parallelization-based on the data parallel paradigm and work sharing, and enables parallelizing the original sequential code using minimal modification with simple directives, like Open MP. And for flexibility, it allows to combine with explicit MPI coding on parallelization with Open MP for more complicated parallel codes. Experimental results of our implementation show that Open MPD achieves three to eight times speed-up on a PC cluster with eight processors given a small modification to the original sequential code.

关键词： Arrays Synchronization Programming Libraries Reactive power Program processors Memory architecture

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Large-scale computing for protein-protein binding free energy calculation

Large-scale computing for protein-protein binding free energ...

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2008 International Conference on Parallel and Distributed processing Techniques and Applications, PDPTA 2008

作者： Ikeda, Junichi Ohno, Kazuki Akioka, Sayaka Orita, Masaya Muraoka, Yoichi Noguchi, Tamotsu Sekijima, Masakazu Computational Biology Research Center National Institute of Advanced Industrial Science and Technology Japan Graduate School of Fundarmental Science and Engineering Waseda University Japan Drug Discovery Research Astellas Pharma Inc. Japan Graduate School of Information Systems University of Electro-Communications Japan

Infomation on binding free energy is important for understanding interactions between proteins. In this paper, we introduce an evaluation system for binding free energy of proteins, which applies Shirts' algorithm... 详细信息

ISBN: (纸本)1601320841

关键词： Proteins

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IEEE Transactions on Haptics: Editorial

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IEEE Transactions on Haptics 2008年第1期1卷 2-8页

作者： Edward Colgate, J. Lederman, Susan Prattichizzo, Domenico Barbagli, Federico Basdogan, Cagatay Buss, Martin Ernst, Marc Frisoli, Antonio Gillespie, Brent Grant, Danny Harders, Matthias Hayward, Vincent Jones, Lynette Kajimoto, Hiroyuki Kappers, Astrid Kheddar, Abderrahmane Lin, Ming C. MacLean, Karon Miller, Brian Noma, Haruo Okamura, Allison M. O'Malley, Mareia Ryu, Jeha Tan, Hong Z. Yokokohji, Yasuyoshi Department of Psychology School of Computing Queen's University Canada IEEE Robotics and Automation Society Tübingen Germany Stanford University's Computer Science Department Tübingen Germany Institute of Automatic Control Engineering Technische Universität München Germany Independent Research Group Multisensory Perception and Action Max Planck Institute for Biological Cybernetics Tübingen Germany Department of Applied Mechanics SSSA Japan Research Division Virtual Reality and Telerobotic Systems PERCRO Laboratory Japan Department of Mechanical Engineering Japan Department of Robotics McGill University Canada Computer Vision Lab ETH Zurich Japan Virtual Reality in Medicine Group Japan IEEE CS/RAS Technical Committee on Haptics Japan Department of Electrical and Computer Engineering McGill University Canada Department of Mechanical Engineering MIT Japan University of Electro-Communications Japan Department of Physics and Astronomy Utrecht University Netherlands University of Evry France Chapel Hill United States Department of Computer Science University of British Columbia Canada ATR Knowledge Science Lab United Kingdom Department of Mechanical Engineering Denmark Johns Hopkins University United States Laboratory for Computational Sensing and Robotics United Kingdom Engineering Research Center for Computer-Integrated Surgical Systems and Technology United States Mechanical Engineering and Materials Science Department Rice University United States Korea Republic of Department of Electrical and Computer Engineering Mechanical Engineering and Psychological Sciences Purdue University United States Department of Mechanical Engineering and Science Graduate School of Engineering Kyoto University Japan

No abstract available

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Distributed Linear Programming and Resource Management for Data Mining in Distributed Environments

Distributed Linear Programming and Resource Management for D...

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IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Haimonti Dutta Hillol Kargupta Center for Computational Learning Systems Columbia University NY USA Department of Computer Science and Electrical Engineering University of Maryland Baltimore USA

关键词： Linear programming Resource management Data mining Distributed algorithms Distributed computing Large-scale systems Data security Information security Access control Monitoring

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Revealing Disease Related Interactions by Correlation Analysis

Revealing Disease Related Interactions by Correlation Analys...

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第二届最优化与系统生物学国际研讨会

作者： Zi-Kai Wu Zhi-Yong Zhang Lv-Wen Zhang Katsuhisa Horimoto nstitute of Systems Biology Shanghai University School of Communication and Information Engineering Shanghai University School of Computer Engineering and Science Shanghai University Computational Biology Research Center National Institute of Advanced Industrial Science and Technology

The computational identification of disease related lesions is still a key open problem in biomedicine and systems biology. Dysregulated interactions may be an important reason that causes disease. In this paper, we aim to identify dysregulated interactions so as to elucidate the mechanism of disease in a systematic manner. Specially, we present a method to detect which protein-protein interactions or genetic interactions are downregulated or upregulated due to disease process. The proposed method was applied to a human molecular interaction network and a prostate cancer microarray dataset to reveal dysregulated interactions. The enrichment analysis of cancerous genes and disease related GO terms in identified dysregulated interactions shows that the identified dysregulated interactions are disease related, which verifies the effectiveness of our method.

关键词： Network Disease Interaction Correlation

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