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Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

Human genomics 2016年第1期10 Suppl 1卷 12页

作者： A. K. Srivastava Y. Wang R. Huang C. Skinner T. Thompson L. Pollard T. Wood F. Luo R. Stevenson R. Polimanti J. Gelernter X. Lin I. Y. Lim Y. Wu A. L. Teh L. Chen I. M. Aris S. E. Soh M. T. Tint J. L. MacIsaac F. Yap K. Kwek S. M. Saw M. S. Kobor M. J. Meaney K. M. Godfrey Y. S. Chong J. D. Holbrook Y. S. Lee P. D. Gluckman N. Karnani A. Kapoor D. Lee A. Chakravarti C. Maercker F. Graf M. Boutros G. Stamoulis F. Santoni P. Makrythanasis A. Letourneau M. Guipponi N. Panousis M. Garieri P. Ribaux E. Falconnet C. Borel S. E. Antonarakis S. Kumar J. Curran J. Blangero S. Chatterjee J. Akiyama D. Auer C. Berrios L. Pennacchio T. R. Donti G. Cappuccio M. Miller P. Atwal A. Kennedy A. Cardon C. Bacino L. Emrick J. Hertecant F. Baumer B. Porter M. Bainbridge P. Bonnen B. Graham R. Sutton Q. Sun S. Elsea Z. Hu P. Wang Y. Zhu J. Zhao M. Xiong David A. Bennett A. Hidalgo-Miranda S. Romero-Cordoba S. Rodriguez-Cuevas R. Rebollar-Vega E. Tagliabue M. Iorio E. D’Ippolito S. Baroni B. Kaczkowski Y. Tanaka H. Kawaji A. Sandelin R. Andersson M. Itoh T. Lassmann Y. Hayashizaki P. Carninci A. R. R. Forrest C. A. Semple E. A. Rosenthal B. Shirts L. Amendola C. Gallego M. Horike-Pyne A. Burt P. Robertson P. Beyers C. Nefcy D. Veenstra F. Hisama R. Bennett M. Dorschner D. Nickerson J. Smith K. Patterson D. Crosslin R. Nassir N. Zubair T. Harrison U. Peters G. Jarvik F. Menghi K. Inaki X. Woo P. Kumar K. Grzeda A. Malhotra H. Kim D. Ucar P. Shreckengast K. Karuturi J. Keck J. Chuang E. T. Liu B. Ji A. Tyler G. Ananda G. Carter H. Nikbakht M. Montagne M. Zeinieh A. Harutyunyan M. Mcconechy N. Jabado P. Lavigne J. Majewski J. B. Goldstein M. Overman G. Varadhachary R. Shroff R. Wolff M. Javle A. Futreal D. Fogelman L. Bravo W. Fajardo H. Gomez C. Castaneda C. Rolfo J. A. Pinto K. C. Akdemir L. Chin S. Patterson C. Statz S. Mockus S. N. Nikolaev X. I. Bonilla L. Parmentier B. King F. Bezrukov G. Kaya V. Zoete V. Seplyarskiy H. Sharpe T. McKee K. Popadin N. Basset-Seguin R. Ben Chaabene M. Andrianova C. Verdan K. Grosdemange O. Sumara M. E JCSRI Greenwood Genetic Center Greenwood USA School of Computing Clemson University Clemson USA Biochemical Genetics Laboratory Greenwood Genetic Center Greenwood USA Department Psychiatry Yale Sch Med and VA CT Healthcare Center West Haven USA Department Genetics Yale Sch Med and VA CT Healthcare Center West Haven USA Department Neurobiology Yale Sch Med and VA CT Healthcare Center West Haven USA Singapore Institute for Clinical Sciences Singapore Singapore National University of Singapore Singapore Singapore University of British Columbia Vancouver Canada KK Women’s and Children’s Hospital Singapore Singapore University of Southampton and University Hospital Southampton NHS Foundation Trust Southampton UK University of Auckland Auckland New Zealand McKusick-Nathans Institute of Genetic Medicine Johns Hopkins University School of Medicine Baltimore USA Esslingen University of Applied Sciences Esslingen Germany German Cancer Research Center Heidelberg Germany Department of Genetic Medicine and Development University of Geneva Medical School Geneva Switzerland Geneva University Hospitals-HUG Service of Genetic Medicine Geneva Switzerland GE3 Institute of Genetics and Genomics of Geneva University of Geneva Medical School Geneva Switzerland South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Edinburg USA South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Brownsville USA Institute of Genetic Medicine Johns Hopkins University Baltimore USA Genomics Division Lawrence Berkeley National Laboratory Berkeley USA Molecular and Human Genetics Baylor College of Medicine Houston USA Department of Translational Medical Sciences Federico II University Naples Italy Metabolon Inc Durham USA Section of Pediatric Neurology and Neuroscience Baylor College of Medicine Houston USA Tawam Hospital Abu Dhabi United Arab Emirates Stanford Medical School Stanford USA Sch

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s

关键词： Pulmonary Arterial Hypertension Oral Squamous Cell Carcinoma Deep Neural Network Autosomal Recessive Polycystic Kidney Disease Whole Genome Bisulfite Sequencing

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

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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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Erratum: Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

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Nature communications 2017年第1期8卷 1414页

作者： M Carola Zillikens Serkalem Demissie Yi-Hsiang Hsu Laura M Yerges-Armstrong Wen-Chi Chou Lisette Stolk Gregory Livshits Linda Broer Toby Johnson Daniel L Koller Zoltán Kutalik Jian'an Luan Ida Malkin Janina S Ried Albert V Smith Gudmar Thorleifsson Liesbeth Vandenput Jing Hua Zhao Weihua Zhang Ali Aghdassi Kristina Åkesson Najaf Amin Leslie J Baier Inês Barroso David A Bennett Lars Bertram Rainer Biffar Murielle Bochud Michael Boehnke Ingrid B Borecki Aron S Buchman Liisa Byberg Harry Campbell Natalia Campos Obanda Jane A Cauley Peggy M Cawthon Henna Cederberg Zhao Chen Nam H Cho Hyung Jin Choi Melina Claussnitzer Francis Collins Steven R Cummings Philip L De Jager Ilja Demuth Rosalie A M Dhonukshe-Rutten Luda Diatchenko Gudny Eiriksdottir Anke W Enneman Mike Erdos Johan G Eriksson Joel Eriksson Karol Estrada Daniel S Evans Mary F Feitosa Mao Fu Melissa Garcia Christian Gieger Thomas Girke Nicole L Glazer Harald Grallert Jagvir Grewal Bok-Ghee Han Robert L Hanson Caroline Hayward Albert Hofman Eric P Hoffman Georg Homuth Wen-Chi Hsueh Monica J Hubal Alan Hubbard Kim M Huffman Lise B Husted Thomas Illig Erik Ingelsson Till Ittermann John-Olov Jansson Joanne M Jordan Antti Jula Magnus Karlsson Kay-Tee Khaw Tuomas O Kilpeläinen Norman Klopp Jacqueline S L Kloth Heikki A Koistinen William E Kraus Stephen Kritchevsky Teemu Kuulasmaa Johanna Kuusisto Markku Laakso Jari Lahti Thomas Lang Bente L Langdahl Lenore J Launer Jong-Young Lee Markus M Lerch Joshua R Lewis Lars Lind Cecilia Lindgren Yongmei Liu Tian Liu Youfang Liu Östen Ljunggren Mattias Lorentzon Robert N Luben William Maixner Fiona E McGuigan Carolina Medina-Gomez Thomas Meitinger Håkan Melhus Dan Mellström Simon Melov Karl Michaëlsson Braxton D Mitchell Andrew P Morris Leif Mosekilde Anne Newman Carrie M Nielson Jeffrey R O'Connell Ben A Oostra Eric S Orwoll Aarno Palotie Stephen C J Parker Munro Peacock Markus Perola Annette Peters Ozren Polasek Richard L Prince Katri Räikkönen Stuart H Ralston Samuli Ripatti John A Robbins Jerome I Rotter Igor Rudan Veikko Department of Internal Medicine Erasmus MC Rotterdam 3000 The Netherlands. Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA) Leiden 2593 The Netherlands. Department of Biostatistics Boston University School of Public Health Boston MA 02118 USA. Hebrew SeniorLife Institute for Aging Research Roslindale MA 02131 USA. Harvard Medical School Boston MA 02115 USA. Molecular and Integrative Physiological Sciences Program Harvard School of Public Health Boston MA 02115 USA. Program in Personalized and Genomic Medicine and Department of Medicine Division of Endocrinology Diabetes and Nutrition University of Maryland School of Medicine Baltimore MD 21201 USA. Broad Institute Cambridge MA 02142 USA. Sackler Faculty of Medicine Department of Anatomy and Anthropology Tel Aviv University Tel Aviv 6997801 Israel. Department of Twin Research and Genetic Epidemiology King's College London St Thomas' Campus London WC2R 2LS UK. Department of Epidemiology Erasmus MC Rotterdam 3000 The Netherlands. Department of Medical Genetics University of Lausanne Lausanne 1011 Switzerland. Swiss Institute of Bioinformatics Lausanne 1015 Switzerland. Centre Hospitalier Universitaire (CHUV) University Institute for Social and Preventive Medicine Lausanne 1010 Switzerland. Department of Medical and Molecular Genetics Indiana University School of Medicine Indianapolis IN 46202 USA. MRC Epidemiology Unit University of Cambridge School of Clinical Medicine Cambridge Biomedical Campus Cambridge CB2 OQQ UK. Institute of Epidemiology II Helmholtz Zentrum München - German Research Center for Environmental Health Neuherberg 85764 Germany. Icelandic Heart Association Kopavogur 201 Iceland. Faculty of Medicine University of Iceland Reykjavik 101 Iceland. deCODE Genetics Reykjavik 101 Iceland. Department of Internal Medicine Institute of Medicine Sahlgrenska Academy University of Gothenburg Gothenburg SE-405 30 Sweden. Dep

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Dynamical Influence of Nodes Revisited: A Markov Chain Analysis of Epidemic Process on Networks

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Chinese Physics Letters 2012年第4期29卷 248-251页

作者： LI Ping ZHANG Jie XU Xiao-Ke SMALL Michael Center for Networked Systems School of Computer ScienceSouthwest Petroleum UniversityChengdu 610500 State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation Southwest Petroleum UniversityChengdu 610500 Center for Computational Systems Biology Fudan UniversityShanghai 200433 Hong Kong Polytechnic University Hung HomKowloonHong Kong School of Communication and Electronic Engineering Qingdao Technological UniversityQingdao 2665206 School of Mathematics and Statistics University of Western AustraliaCrawleyWA 6009Australia

We provide a theoretical analysis of node importance from the perspective of dynamical processes on *** particular,using Markov chain analysis of the susceptible-infected-susceptible (SIS) epidemic model on networks,we derive the node importance in terms of dynamical behaviors on network in a theoretical *** is found that this quantity happens to be the eigenvector centrality under some conditions,which bridges the topological centrality measure of the nodes with the dynamical influence of the nodes for the dynamical *** furthermore discuss the condition under which the eigenvector centrality is valid for dynamical phenomena on networks.

关键词： process dynamical eigenvector

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Joint Analysis of BICEP2/Keck Array and Planck Data

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Physical Review Letters 2015年第10期114卷 101301-101301页

作者： P. A. R. Ade N. Aghanim Z. Ahmed R. W. Aikin K. D. Alexander M. Arnaud J. Aumont C. Baccigalupi A. J. Banday D. Barkats R. B. Barreiro J. G. Bartlett N. Bartolo E. Battaner K. Benabed A. Benoît A. Benoit-Lévy S. J. Benton J.-P. Bernard M. Bersanelli P. Bielewicz C. A. Bischoff J. J. Bock A. Bonaldi L. Bonavera J. R. Bond J. Borrill F. R. Bouchet F. Boulanger J. A. Brevik M. Bucher I. Buder E. Bullock C. Burigana R. C. Butler V. Buza E. Calabrese J.-F. Cardoso A. Catalano A. Challinor R.-R. Chary H. C. Chiang P. R. Christensen L. P. L. Colombo C. Combet J. Connors F. Couchot A. Coulais B. P. Crill A. Curto F. Cuttaia L. Danese R. D. Davies R. J. Davis P. de Bernardis A. de Rosa G. de Zotti J. Delabrouille J.-M. Delouis F.-X. Désert C. Dickinson J. M. Diego H. Dole S. Donzelli O. Doré M. Douspis C. D. Dowell L. Duband A. Ducout J. Dunkley X. Dupac C. Dvorkin G. Efstathiou F. Elsner T. A. Enßlin H. K. Eriksen E. Falgarone J. P. Filippini F. Finelli S. Fliescher O. Forni M. Frailis A. A. Fraisse E. Franceschi A. Frejsel S. Galeotta S. Galli K. Ganga T. Ghosh M. Giard E. Gjerløw S. R. Golwala J. González-Nuevo K. M. Górski S. Gratton A. Gregorio A. Gruppuso J. E. Gudmundsson M. Halpern F. K. Hansen D. Hanson D. L. Harrison M. Hasselfield G. Helou S. Henrot-Versillé D. Herranz S. R. Hildebrandt G. C. Hilton E. Hivon M. Hobson W. A. Holmes W. Hovest V. V. Hristov K. M. Huffenberger H. Hui G. Hurier K. D. Irwin A. H. Jaffe T. R. Jaffe J. Jewell W. C. Jones M. Juvela A. Karakci K. S. Karkare J. P. Kaufman B. G. Keating S. Kefeli E. Keihänen S. A. Kernasovskiy R. Keskitalo T. S. Kisner R. Kneissl J. Knoche L. Knox J. M. Kovac N. Krachmalnicoff M. Kunz C. L. Kuo H. Kurki-Suonio G. Lagache A. Lähteenmäki J.-M. Lamarre A. Lasenby M. Lattanzi C. R. Lawrence E. M. Leitch R. Leonardi F. Levrier A. Lewis M. Liguori P. B. Lilje M. Linden-Vørnle M. López-Caniego P. M. Lubin M. Lueker J. F. Macías-Pérez B. Maffei D. Maino N. Mandolesi A. Mangilli M. Maris P. G. Martin E. Martínez-González S. Masi P. Mason S. Matarrese K. G. Megerian School of Physics and Astronomy Cardiff University Queens Buildings The Parade Cardiff CF24 3AA United Kingdom Institut d’Astrophysique Spatiale CNRS (UMR8617) Université Paris-Sud 11 Bâtiment 121 Orsay France Department of Physics Stanford University Stanford California 94305 USA California Institute of Technology Pasadena California USA Harvard-Smithsonian Center for Astrophysics 60 Garden Street MS 42 Cambridge Massachusetts 02138 USA Laboratoire AIM IRFU/Service d’Astrophysique–CEA/DSM–CNRS–Université Paris Diderot Bâtiment 709 CEA-Saclay F-91191 Gif-sur-Yvette Cedex France SISSA Astrophysics Sector via Bonomea 265 34136 Trieste Italy Université de Toulouse UPS-OMP IRAP F-31028 Toulouse cedex 4 France CNRS IRAP 9 Avenue colonel Roche BP 44346 F-31028 Toulouse cedex 4 France Joint ALMA Observatory Vitacura Santiago Chile Instituto de Física de Cantabria (CSIC-Universidad de Cantabria) Avenida de los Castros s/n Santander Spain APC AstroParticule et Cosmologie Université Paris Diderot CNRS/IN2P3 CEA/lrfu Observatoire de Paris Sorbonne Paris Cité 10 rue Alice Domon et Léonie Duquet 75205 Paris Cedex 13 France Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive Pasadena California USA Dipartimento di Fisica e Astronomia G. Galilei Università degli Studi di Padova via Marzolo 8 35131 Padova Italy Istituto Nazionale di Fisica Nucleare Sezione di Padova via Marzolo 8 I-35131 Padova Italy University of Granada Departamento de Física Teórica y del Cosmos Facultad de Ciencias Granada Spain University of Granada Instituto Carlos I de Física Teórica y Computacional Granada Spain Institut d’Astrophysique de Paris CNRS (UMR7095) 98 bis Boulevard Arago F-75014 Paris France UPMC Université de Paris 06 UMR7095 98 bis Boulevard Arago F-75014 Paris France Institut Néel CNRS Université Joseph Fourier Grenoble I 25 rue des Martyrs Grenoble France Department of Physics and Astronomy University College London L

We report the results of a joint analysis of data from BICEP2/Keck Array and Planck. BICEP2 and Keck Array have observed the same approximately 400 deg2 patch of sky centered on RA 0 h, Dec. −57.5°. The combined maps reach a depth of 57 nK deg in Stokes Q and U in a band centered at 150 GHz. Planck has observed the full sky in polarization at seven frequencies from 30 to 353 GHz, but much less deeply in any given region (1.2 μK deg in Q and U at 143 GHz). We detect 150×353 cross-correlation in B modes at high significance. We fit the single- and cross-frequency power spectra at frequencies ≥150 GHz to a lensed-ΛCDM model that includes dust and a possible contribution from inflationary gravitational waves (as parametrized by the tensor-to-scalar ratio r), using a prior on the frequency spectral behavior of polarized dust emission from previous Planck analysis of other regions of the sky. We find strong evidence for dust and no statistically significant evidence for tensor modes. We probe various model variations and extensions, including adding a synchrotron component in combination with lower frequency data, and find that these make little difference to the r constraint. Finally, we present an alternative analysis which is similar to a map-based cleaning of the dust contribution, and show that this gives similar constraints. The final result is expressed as a likelihood curve for r, and yields an upper limit r0.05<0.12 at 95% confidence. Marginalizing over dust and r, lensing B modes are detected at 7.0σ significance.

关键词： STOKES equations FREQUENCIES of oscillating systems POWER spectra GRAVITATIONAL waves

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Predicting slice loss distortion in H.264/AVC video for low complexity data prioritization

Predicting slice loss distortion in H.264/AVC video for low ...

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IEEE International Conference on Image Processing

作者： Seethal Paluri Kashyap K. R. Kambhatla Sunil Kumar Barbara Bailey Pamela Cosman John Matyjas Computational Science Research Center San Diego State University USA Department of Electrical and Computer Engineering University of California San Diego USA Department of Electrical and Computer Engineering San Diego State University USA Department of Mathematics and Statistics San Diego State University USA Air Force Research Laboratory Rome NY USA

We propose a low complexity Generalized Linear Model (GLM) for prioritizing slices during real-time H.264/AVC compressed video streaming. We train the GLM over a video database to predict the Cumulative Mean Square Error (CMSE) corresponding to individual slice losses by using a combination of efficient video parameters which can be easily extracted during the encoding of a frame. We prioritize the slices generated within a Group of Pictures (GOP) based on the predicted CMSE by using a Quartile Based Prioritization (QBP) scheme. For comparison, we also perform QBP on measured CMSE values from individual pre-encoded slice losses and analyze the priority misclassifications of the slices. We validate our model by applying Unequal Error Protection (UEP) using RCPC codes to the different prioritized bitstreams and evaluating their performance over noisy channels. Simulation results show that predicted CMSE schemes achieve PSNR performance close to that of the measured CMSE schemes for different slice sizes, video bitrates and over different channel SNRs.

关键词： computational modeling Streaming media Loss measurement Predictive models Video coding AWGN channels Bit rate

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3D object retrieval using an efficient and compact hybrid shape descriptor

3D object retrieval using an efficient and compact hybrid sh...

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1st Eurographics Workshop on 3D Object Retrieval, EG 3DOR 2008

作者： Papadakis, P. Pratikakis, I. Theoharis, T. Passalis, G. Perantonis, S. National Center for Scientific Research Demokritos Computational Intelligence Laboratory Institute of Informatics and Telecommunications Agia Paraskevi Athens Greece Department of Informatics and Telecommunications Computer Graphics Group National and Capodistrian University of Athens Greece

ISBN: (纸本)9783905674057

We present a novel 3D object retrieval method that relies upon a hybrid descriptor which is composed of 2D features based on depth buffers and 3D features based on spherical harmonics. To compensate for rotation, two alignment methods, namely CPCA and NPCA, are used while compactness is supported via scalar feature quantization to a set of values that is further compressed using Huffman coding. The superior performance of the proposed retrieval methodology is demonstrated through an extensive comparison against state-of-the-art methods on standard datasets. © The Eurographics Association 2008.

关键词： Object recognition

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SHREC'08 Entry: 2D/3D Hybrid

SHREC'08 Entry: 2D/3D Hybrid

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International Conference on Shape Modeling and Applications

作者： Panagiotis Papadakis Ioannis Pratikakis Stavros Perantonis Theoharis Theoharis Georgios Passalis Computational Intelligence Laboratory Institute of Informatics and Telecommunications National Center for Scientific Research Demokritos Athens Greece Computer Graphics Group Department of Informatics and Telecommunications National and Kapodistrian University of Athens Greece

In this paper, we present an overview of the 3D object retrieval method that we employed in our participation to the generic models track of SHREC 2008 organized by the AIM@SHAPE network of excellence. The proposed methodology is detailed in [2]. Our method is based on a hybrid scheme where 2D features as well as 3D features are extracted from a 3D model which has been previously normalized for rotation using two alternative alignment techniques. The alignment methods that are used are CPCA and NPCA. The 2D features are Fourier coefficients extracted from a set of depth buffers and the 3D features are spherical harmonic coefficients extracted from a spherical function-based representation of a 3D model.

关键词： Feature extraction Data mining Information retrieval Electronic mail Informatics computational intelligence computer graphics

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Identifying interaction sites in "Recalcitrant" proteins: Predicted protein and RNA binding sites in REV proteins of HIV-1 and EIAV agree with experimental data

Identifying interaction sites in "Recalcitrant" proteins: Pr...

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11th Pacific Symposium on Biocomputing 2006, PSB 2006

作者： Terribllini, Michael Lee, Jae-Hyung Yan, Changhui Jernigan, Robert L. Carpenter, Susan Honavar, Vasant Dobbs, Drena Bioinformatics and Computational Biology Graduate Program LH. Baker Center for Bioinformatics and Biological Statistics Iowa State University Ames IA 50010 United States Department of Computer Science Iowa State University Ames IA 50010 United States Department of Biochemistry Biophysics and Molecular Biology Iowa State University Ames IA 50010 United States Department of Genetics Development and Cell Biology Iowa State University Ames IA 50010 United States Artificial Intelligence Research Laboratory Center for Computational Intelligence Learning and Discovery Iowa State University Ames IA 50010 United States Department of Veterinary Microbiology and Pathology Washington State University Pullman WA. 99164 United States

ISBN: (纸本)9812564632

Protein-protein and protein nucleic acid interactions are vitally important for a wide range of biological processes, including regulation or gene expression, protein synthesis, and replication and assembly of many viruses. We have developed machine learning approaches for predicting which amino acids of a protein participate in its interactions with other proteins and/or nucleic acids, using only the proiein sequence as input. In this paper, we describe an application of classifiers trained on datasets of well-characterized protein-protein and protein-RNA complexes for which experimental structures are available. We apply these classifiers to the problem of predicting protein and RNA binding sites in the sequence of a clinically important protein for which the structure is not known: the regulatory protein Rev, essential for the replication of HIV-I and other lentiviruses. We compare our predictions with published biochemical, genetic and partial structural information for HIV-1 and EIAV Rev and with our own published experimental mapping of RNA binding sites in EIAV Rev. The predicted and experimentally determined binding sites are in very good agreement. The ability to predict reliably the residues of a protein that directly contribute to specific binding events - without the requirement for structural information regarding either the protein or complexes in which it participates - can potentially generate new disease intervention strategies.

关键词： Binding sites

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Radiation-coupled front-tracking simulations for laser-driven shock experiments

Radiation-coupled front-tracking simulations for laser-drive...

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作者： Zhang, Yongmin Drake, R. Paul Glimm, James Grove, John W. Sharp, David H. Department of Applied Mathematics and Statistics University at Stony Brook Stony Brook NY 11974-3600 United States University of Michigan 2455 Hayward St. Ann Arbor MI 48105 United States Center for Data Intensive Computing Brookhaven National Laboratory Upton NY 11793-6000 United States Continuum Dynamics Group Computer and Computational Science Division Los Alamos National Laboratory Los Alamos NM 87545 United States Complex Systems Group Theoretical Division Los Alamos National Laboratory Los Alamos NM 87545 United States

The purpose of this paper is to develop a numerical algorithm to track the preheat interface motion driven by radiation transfer in high-intensity laser experiments. Our front-tracking algorithm is coupled to a radiation process through an inter-package coupling by connecting the output from a radhydro code HYADES to the input of FronTier code of front tracking. Our coupled algorithm is validated by comparing simulation results from both codes in both low and high radiation cases. Significant interface motion and deformation of the harmonic perturbation due to radiation preheat are observed in high radiation heat case. © 2005 Elsevier Ltd. All rights reserved.

关键词： Algorithms

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