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2012全国植物生物学大会

作者： Shan Wang Yanbin Yin Qin Ma Xiaojia Tang Dongyun Hao Ying Xu Key Lab for Molecular Enzymology and Engineering of the Ministry of Education Jilin UniversityChangchun China College of Computer Science and Technology Jilin University Changchun China Biotechnology Research Centre Jilin Academy of Agricultural Sciences (JAAS) Changchun China Computational Systems Biology Laboratory Department of Biochemistry and Molecular Biology and Institute of Bioinformatics BESC BioEerngy Science Center University of Georgia Athens GA USA BESC BioEerngy Science Center University of Georgia Athens GA USA Computational Systems Biology Laboratory Department of Biochemistry and Molecular Biology and Institute of Bioinformatics Key Lab for Molecular Enzymology and Engineering of the Ministry of Education Jilin UniversityChangchun China Computational Systems Biology Laboratory Department of Biochemistry and Molecular Biology and Institute of Bioinformatics

Identification of the novel genes relevant to plant cell-wall (PCW) synthesis represents a highly important and challenging *** substantial efforts have been invested into studying this problem, the vast majority of t... 详细信息

关键词： Plant cell wall Arabidopsis Co-expression network analyses Bi-clustering Cis regulatory motifs

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A survey of the initialization of centers and widths in radial basis function network for classification

A survey of the initialization of centers and widths in radi...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Chun-Ru Dong Patrick P. K. Chan Wing W. Y. Ng Daniel S. Yeung Key Laboratory of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding China Machine Learning and Cybernetics Research Center School of Computer Science and Engineering South China University of Technology Guangzhou China

The radial basis function network (RBFN) has been widely used in various fields such as function regression, pattern recognition, and error detection, etc. However, the structural parameters of RBFN including the number of hidden units, centers vectors, and widths (variances) are one of the most important issues when training a RBFN, which greatly affect the performance of RBFN. So, the objective of this paper is to construct an elementary survey about this problem. Firstly, the fundamental knowledge and notations of RBFN is introduced. Secondly, we summarize most existing network structure initialization methods for RBFN and categorize them into four goups. Then some typical appraoches for each category are introduced and discussed. The disadvantages and virtues for parts of methods are also introduced. Finally, the paper is concluded with a discussion of current difficulties and possible future directions about RBFN architecture selection.

关键词： Training Neurons Artificial neural networks Clustering algorithms Optimization Machine learning

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Data Mining in Earth System Science (DMESS 2011)

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Procedia computer Science 2011年 4卷 1450-1455页

作者： Forrest M. Hoffman J. Walter Larson Richard Tran Mills Bjørn-Gustaf J. Brooks Auroop R. Ganguly William W. Hargrove Jian Huang Jitendra Kumar Ranga R. Vatsavai Computational Earth Sciences Group Oak Ridge National Laboratory Oak Ridge TN USA Department of Earth System Science University of California Irvine CA USA Mathematics and Computer Science Division Argonne National Laboratory Argonne IL USA Computation Institute University of Chicago/Argonne National Laboratory Chicago IL USA School of Computer Science The Australian National University Canberra ACT AUSTRALIA Department of Electrical Engineering & Computer Science University of Tennessee Knoxville TN USA Center for Climatic Research University of Wisconsin Madison WI USA Geographic Information Science and Technology Group Oak Ridge National Laboratory Oak Ridge TN USA Eastern Forest Environmental Threat Assessment Center (EFETAC) USDA Forest Service Asheville NC USA

From field-scale measurements to global climate simulations and remote sensing, the growing body of very large and long time series Earth science data are increasingly difficult to analyze, visualize, and interpret. Data mining, information theoretic, and machine learning techniques—such as cluster analysis, singular value decomposition, block entropy, Fourier and wavelet analysis, phase-space reconstruction, and artificial neural networks—are being applied to problems of segmentation, feature extraction, change detection, model-data comparison, and model validation. The size and complexity of Earth science data exceed the limits of most analysis tools and the capacities of desktop computers. New scalable analysis and visualization tools, running on parallel cluster computers and supercomputers, are required to analyze data of this magnitude. This workshop will demonstrate how data mining techniques are applied in the Earth sciences and describe innovative computer science methods that support analysis and discovery in the Earth sciences.

关键词： Data mining Remote sensing High performance computing Segmentation Change detection Synthesis visualization

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Clustering algorithms in biomedical research: A review

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IEEE Reviews in Biomedical engineering 2010年 3卷 120-154页

作者： Xu, Rui Wunsch, Donald C. Applied Computational Intelligence Laboratory GE Global Research Center Niskayuna NY 12309 United States Applied Computational Intelligence Laboratory Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO 65409 United States

Applications of clustering algorithms in biomedical research are ubiquitous, with typical examples including gene expression data analysis, genomic sequence analysis, biomedical document mining, and MRI image analysis. However, due to the diversity of cluster analysis, the differing terminologies, goals, and assumptions underlying different clustering algorithms can be daunting. Thus, determining the right match between clustering algorithms and biomedical applications has become particularly important. This paper is presented to provide biomedical researchers with an overview of the status quo of clustering algorithms, to illustrate examples of biomedical applications based on cluster analysis, and to help biomedical researchers select the most suitable clustering algorithms for their own applications. © 2010 IEEE.

关键词： Neural networks

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Relationships and data sanitization: A study in scarlet 10

Relationships and data sanitization: A study in scarlet

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Proceedings of the 2010 New Security Paradigms Workshop

作者： Bishop, Matt Cummins, Justin Peisert, Sean Singh, Anhad Bhumiratana, Bhume Agarwal, Deborah Frincke, Deborah Hogarth, Michael Dept. of Computer Science University of California at Davis Davis CA 95616-8562 United States Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 United States Dept. of Computer Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand Pacific Northwest National Laboratory Richland WA 99352 United States Dept. of Pathology and Laboratory Medicine University of California Davis Health System Sacramento CA 95820 United States

ISBN: (纸本)9781450304153

research in data sanitization (including anonymization) emphasizes ways to prevent an adversary from desanitizing data. Most work focuses on using mathematical mappings to sanitize data. A few papers examine incorporation of privacy requirements, either in the guise of templates or prioritization. Essentially these approaches reduce the information that can be gleaned from a data set. In contrast, this paper considers both the need to ''desanitize'' and the need to support privacy. We consider conflicts between privacy requirements and the needs of analysts examining the redacted data. Our goal is to enable an informed decision about the effects of redacting, and failing to redact data. We begin with relationships among the data being examined, including relationships with a known data set and other, additional, external data. By capturing these relationships, desanitization techniques that exploit them can be identified, and the information that must be concealed in order to thwart them can be determined. Knowing that, a realistic assessment of whether the information and relationships are already widely known or available will enable the sanitizers to assess whether irreversible sanitization is possible, and if so, what to conceal to prevent desanitization. © 2010 ACM.

关键词： Data privacy

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Direct observation of a dispersionless impurity band in hydrogenated graphene

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Physical Review B 2011年第16期83卷 165433-165433页

作者： D. Haberer L. Petaccia M. Farjam S. Taioli S. A. Jafari A. Nefedov W. Zhang L. Calliari G. Scarduelli B. Dora D. V. Vyalikh T. Pichler Ch. Wöll D. Alfè S. Simonucci M. S. Dresselhaus M. Knupfer B. Büchner A. Grüneis IFW Dresden P.O. Box 270116 D-01171 Dresden Germany Elettra Synchrotron Light Laboratory Sincrotrone Trieste SCpA S.S. 14 Km 163.5 34149 Trieste Italy School of Nano Science Institute for Research in Fundamental Sciences (IPM) P.O. Box 19395-5531 Tehran Iran Interdisciplinary Laboratory for Computational Science (LISC) FBK-CMM and University of Trento Via Sommarive 18 I-38123 Trento Italy Department of Physics University of Trento Via Sommarive 14 I-38100 Trento Italy Department of Physics Sharif University of Technology Tehran 11155-9161 Iran Institut für Funktionelle Grenzflächen (IFG) Karlsruher Institut für Technologie (KIT) Hermann-von-Helmholtz-Platz 1 D-76344 Eggenstein-Leopoldshafen Germany National Synchrotron Radiation Laboratory University of Science and Technology of China 230029 Hefei Anhui People’s Republic of China Department of Physics Budapest University of Technology and Economics Budafoki t 8 H-1111 Budapest Hungary Institut für Festkörperphysik TU Dresden Mommsenstrasse 13 D-01069 Dresden Germany Faculty of Physics University of Vienna Strudlhofgasse 4 A-1090 Wien Austria Department of Earth Sciences University College London Gower Street London WC1E 6BT UK Department of Physics and Astronomy University College London Gower Street London WC1E 6BT UK London Centre for Nanotechnology University College London Gower Street London WC1E 6BT UK Department of Physics University of Camerino Via Madonna delle Carceri 9 I-62032 Camerino Italy Department of Physics and Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA 02139-4307 USA

We show with angle-resolved photoemission spectroscopy that a new energy band appears in the electronic structure of electron-doped hydrogenated monolayer graphene (H-graphene). Its occupation can be controlled with the hydrogen amount and allows for tuning of graphene’s doping level. Our calculations of the electronic structure of H-graphene suggest that this state is largely composed of hydrogen 1s orbitals and remains extended for low H coverages despite the random chemisorption of H. Further evidence for the existence of a hydrogen state is provided by x-ray absorption studies of undoped H-graphene which are clearly showing the emergence of an additional state in the vicinity of the π* resonance.

关键词： PHOTOEMISSION SPECTRUM analysis ELECTRONS MONOMOLECULAR films GRAPHENE

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Reports of the AAAI 2010 conference workshops

Reports of the AAAI 2010 conference workshops

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作者： Aha, David W. Boddy, Mark Bulitko, Vadim D'Avila Garcez, Artur S. Doshi, Prashant Edelkamp, Stefan Geib, Christopher Gmytrasiewicz, Piotr Goldman, Robert P. Halevy, Alon Hitzler, Pascal Isbell, Charles Josyula, Darsana Kaelbling, Leslie Pack Kersting, Kristian Kunda, Maithilee Lamb, Luis C. Marthi, Bhaskara McGreggor, Keith Mihalkova, Lilyana Nastase, Vivi Natarajan, Sriraam Provan, Gregory Raja, Anita Ram, Ashwin Riedl, Mark Russell, Stuart Sabharwal, Ashish Smaus, Jan-Georg Sukthankar, Gita Tuyls, Karl Van Der Meyden, Ron Adaptive Systems Section Naval Research Laboratory Washington DC United States Adventium Labs. Minneapolis MN United States Department of Computer Science University of Alberta Canada City University London United Kingdom University of Georgia United States University of Bremen Germany School of Informatics University of Edinburgh United Kingdom University of Illinois Chicago United States Smart Information Flow Technologies LLC Minneapolis MN United States Structured Data Group Google Research United States Department of Computer Science Wright State University Dayton OH United States School of Interactive Computing Georgia Institute of Technology Atlanta GA United States Department of Computer Science Bowie State University United States Department of Computer Science and Engineering Massachusetts Institute of Technology United States Statistical Relational Mining Group Fraunhofer IAIS Germany Department of Computer Science Federal University of Rio Grande Do sul Brazil Willow Garage Inc. CA United States Computer Science Department University of Maryland College Park United States Heidelberg Institute for Theoretical Studies Heidelberg Germany Department of Computer Science University of Wisconsin Madison United States University College Cork Ireland Cork Complex Systems Lab. Ireland Department of Software and Information Systems University of North Carolina Charlotte United States Department of Computer Science and Engineering University of California Berkeley United States Department of Computer Science Cornell University United States Institute for Computational Sustainability United States University of Freiburg Germany School of Electrical Engineering and Computer Science University of Central Florida United States Maastricht University Netherlands University of New South Wales NICTA Australia

The AAAI-10 workshop program was held on July 11-12, 2010, at the Westin Peachtree Plaza in Atlanta, Georgia. The workshop program included 13 workshops covering a wide range of topics in artificial intelligence. There were several presentations on particular formalisms for combining the levels of planning from the perspectives of classical planning, motion planning, POMDPs, search-based planning, and temporal logic-based constraints. Henry Lieberman from Massachusetts Institute of technology Media laboratory presented work developing a platform for knowledge acquisition and usage from expert users, built upon experience with eliciting information from nonexperts in a collaborative manner. The objective of the AAAI Workshop on Goal-Directed Autonomy (GDA) was to encourage discussion and novel contributions on intelligent agents that can self-select their goals. Jeremy Baxter from QinetiQ focused on user interaction, while Nick Hawes described a goal-directed reasoning framework for controlling a mobile robot.

关键词： Motion planning

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Prediction of novel precursor miRNAs using a context-sensitive Hidden Markov Model (CSHMM)

Prediction of novel precursor miRNAs using a context-sensiti...

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8th Asia-Pacific Bioinformatics Conference, APBC 2010

作者： Agarwal, Sumeet Vaz, Candida Bhattacharya, Alok Srinivasan, Ashwin Department of Physics Systems Biology Doctoral Training Centre University of Oxford Parks Road Oxford OX1 3PU United Kingdom Center for Computational Biology and Bioinformatics School of Information Technology Jawaharlal Nehru University New Delhi 110067 India School of Life Sciences Jawaharlal Nehru University New Delhi 110067 India Oxford University Computing Laboratory Wolfson Building Parks Road Oxford OX1 3QD United Kingdom IBM India Research Lab. 4-C Vasant Kunj Institutional Area Phase II Vasant Kunj New Delhi 110070 India School of Computer Science and Engineering Centre for Health Informatics University of New South Wales Sydney Australia

Background: It has been apparent in the last few years that small non coding RNAs (ncRNA) play a very significant role in biological regulation. Among these microRNAs (miRNAs), 22-23 nucleotide small regulatory RNAs, have been a major object of study as these have been found to be involved in some basic biological processes. So far about 706 miRNAs have been identified in humans alone. However, it is expected that there may be many more miRNAs encoded in the human genome. In this report, a "context-sensitive" Hidden Markov Model (CSHMM) to represent miRNA structures has been proposed and tested extensively. We also demonstrate how this model can be used in conjunction with filters as an ab initio method for miRNA identification. Results: The probabilities of the CSHMM model were estimated using known human miRNA sequences. A classifier for miRNAs based on the likelihood score of this "trained" CSHMM was evaluated by: (a) cross-validation estimates using known human sequences, (b) predictions on a dataset of known miRNAs, and (c) prediction on a dataset of non coding RNAs. The CSHMM is compared with two recently developed methods, miPred and CID-miRNA. The results suggest that the CSHMM performs better than these methods. In addition, the CSHMM was used in a pipeline that includes filters that check for the presence of EST matches and the presence of Drosha cutting sites. This pipeline was used to scan and identify potential miRNAs from the human chromosome 19. It was also used to identify novel miRNAs from small RNA sequences of human normal leukocytes obtained by the Deep sequencing (Solexa) methodology. A total of 49 and 308 novel miRNAs were predicted from chromosome 19 and from the small RNA sequences respectively Conclusion: The results suggest that the CSHMM is likely to be a useful tool for miRNA discovery either for analysis of individual sequences or for genome scan. Our pipeline, consisting of a CSHMM and filters to reduce false positives shows promise as

关键词： RNA

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Design of low power parallel multiplier

Design of low power parallel multiplier

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作者： Badghare, Rahul M. Mangal, Sanjiv Kumar Deshmukh, Raghavendra B. Patrikar, Rajendra M. Computational Research Laboratory Pune 411016 India VLSI Design Labs Department of Electronics and Computer Science Engineering Visvesvaraya National Institute of Technology Nagpur 440011 India

Recent trends in the signal processing applications have created a need for energy efficient computation. Multiplication is a major power consuming circuit in many application areas like DSP, cryptography, and communication. This paper presents a novel architecture for the radix-2 Booth recoded multiplier where we remove sign extended bits. The architecture is further optimized using proposed "Booth Recoding Unit" for low power applications. It is done by reducing switching activity on the inputs to the multiplication unit to reduce overall switching activity and hence the dynamic power consumption. We also propose an Adder-Subtractor circuit with reduced switching activity. Test Results show that the proposed design consumes 4 times less power and 15% less area than a conventional radix-2 low power Booth recoded multiplier. Copyright © 2009 American Scientific Publishers All rights reserved Printed in the United States of America.

关键词： Field programmable gate arrays (FPGA)

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Meeting report: the terabase metagenomics workshop and the vision of an Earth microbiome project

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Standards in genomic sciences 2010年第3期3卷 243-8页

作者： Jack A Gilbert Folker Meyer Dion Antonopoulos Pavan Balaji C Titus Brown Christopher T Brown Narayan Desai Jonathan A Eisen Dirk Evers Dawn Field Wu Feng Daniel Huson Janet Jansson Rob Knight James Knight Eugene Kolker Kostas Konstantindis Joel Kostka Nikos Kyrpides Rachel Mackelprang Alice McHardy Christopher Quince Jeroen Raes Alexander Sczyrba Ashley Shade Rick Stevens Argonne National Laboratory Argonne USA Department of Ecology and Evolution University of Chicago Chicago USA College of Engineering Michigan State University East Lansing USA Department of Microbiology and Cell Science University of Florida Gainesville USA Department of Evolution and Ecology University of California Davis USA DOE Joint Genome Institute Walnut Creek USA Illumina Saffron Walden UK NERC Centre for Ecology and Hydrology UK Department of Computer Science and Department of Electrical & Computer Engineering Virginia Tech Blacksburg USA Department of Cancer Biology and Translational Science Institute Wake Forest University Winston-Salem USA Center for Bioinformatics ZBIT Tübingen University Tübingen Germany Earth Sciences Division Lawrence Berkeley National Laboratory Berkeley USA Department of Chemistry and Biochemistry Boulder USA Roche-454 Branford USA Seattle Children’s Hospital Seattle USA School of Civil and Environmental Engineering and School of Biology Georgia Institute of Technology Atlanta USA The Florida State University Tallahassee USA Department of Algorithmic Bioinformatics Heinrich-Heine University Düsseldorf Germany Max-Planck Research Group for Computational Genomics and Epidemiology Max-Planck-Institut fur Informatik Saarbrücken Germany Department of Civil Engineering University of Glasgow Glasgow UK Department of Molecular and Cellular Interactions VIB - University of Brussels Brussels Belgium Department of Molecular Cellular and Developmental Biology Yale University New Haven USA

Between July 18(th) and 24(th) 2010, 26 leading microbial ecology, computation, bioinformatics and statistics researchers came together in Snowbird, Utah (USA) to discuss the challenge of how to best characterize the microbial world using next-generation sequencing technologies. The meeting was entitled "Terabase Metagenomics" and was sponsored by the Institute for Computing in Science (ICiS) summer 2010 workshop program. The aim of the workshop was to explore the fundamental questions relating to microbial ecology that could be addressed using advances in sequencing potential. Technological advances in next-generation sequencing platforms such as the Illumina HiSeq 2000 can generate in excess of 250 billion base pairs of genetic information in 8 days. Thus, the generation of a trillion base pairs of genetic information is becoming a routine matter. The main outcome from this meeting was the birth of a concept and practical approach to exploring microbial life on earth, the Earth Microbiome Project (EMP). Here we briefly describe the highlights of this meeting and provide an overview of the EMP concept and how it can be applied to exploration of the microbiome of each ecosystem on this planet.

关键词： Microbial Community Microbial Genome Metabolic Flux Analysis Metagenomic Data Human Microbiome Project

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