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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： G. A. Dominguez M. Kamezaki M. French S. Sugano Graduate Program for Embodiment Informatics for Leading Graduate Schools Japan Research Institute for Science and Engineering (RISE) Waseda University Tokyo Japan Graduate Program for Embodiment Informatics for Leading Graduate Schools Waseda University Tokyo Japan Department of Modern Mechanical Engineering Waseda University Shinjuku-ku Tokyo Japan

A new design of a magnetorheological piston prototype intended for passive or active force control in robotic applications for human robot interaction is introduced. It is based in a novel toroidal array of valves, contained within the piston head, which are used to control the output force of the actuator in order to achieve a high degree of reliability, size efficiency, and safety, by exploiting the material properties of magnetorheological fluids and permalloy metals. This paper describes the main points in the development of the magnetorheological piston prototype, the mathematical modelling of the magnetic circuit, and the results of the experiments conducted using a universal testing machine to evaluate the passive performance of the prototype. Results show the feasibility and performance of the new toroidal magnetic circuit of the magnetorheological hydraulic piston prototype. Improvements in order to be able to test the active performance of the design together with a pump setup are proposed.

关键词： Pistons Toroidal magnetic fields Magnetomechanical effects Magnetic heads Actuators Magnetic circuits Valves

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Microphone-accelerometer based 3D posture estimation for a hose-shaped rescue robot

Microphone-accelerometer based 3D posture estimation for a h...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Y. Bando K. Itoyama M. Konyo S. Tadokoro K. Nakadai K. Yoshii H. G. Okuno Graduate School of Informatics Kyoto University Kyoto Japan Graduate School of Information Science Tohoku University Miyagi Japan Graduate School of Information Science and Engineering Honda Research Institute Japan Co. Ltd. Saitama Japan Graduate Program for Embodiment Informatics Waseda University Tokyo Japan

3D posture estimation for a hose-shaped robot is critical in rescue activities due to complex physical environments. Conventional sound-based posture estimation assumes rather flat physical environments and focuses only on 2D, resulting in poor performance in real world environments with rubble. This paper presents novel 3D posture estimation by exploiting microphones and accelerometers. The idea of our method is to compensate the lack of posture information obtained by sound-based time-difference-of arrival (TDOA) with the tilt information obtained from accelerometers. This compensation is formulated as a nonlinear state-space model and solved by the unscented Kalman filter. Experiments are conducted by using a 3m hose-shaped robot with eight units of a microphone and an accelerometer and seven units of a loudspeaker and a vibration motor deployed in a simple 3D structure. Experimental results demonstrate that our method reduces the errors of initial states to about 20 cm in the 3D space. If the initial errors of initial states are less than 20 %, our method can estimate the correct 3D posture in real-time.

关键词： Microphones Accelerometers Loudspeakers Estimation Robot sensing systems Three-dimensional displays

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Human-voice enhancement based on online RPCA for a hose-shaped rescue robot with a microphone array

Human-voice enhancement based on online RPCA for a hose-shap...

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IEEE International Workshop on Safety, Security, and Rescue Robotics (SSRR)

作者： Yoshiaki Bando Katsutoshi Itoyama Masashi Konyo Satoshi Tadokoro Kazuhiro Nakadai Kazuyoshi Yoshii Hiroshi G. Okuno Graduate School of Informatics Kyoto University Kyoto Japan Graduate School of Information Science Honda Research Institute Japan Co. Ltd Miyagi Japan Graduate School of Information Science and Engineering Tokyo Institute of Technology Saitama Japan Graduate Program for Embodiment Informatics Waseda University Tokyo Japan

This paper presents an online real-time method that enhances human voices included in severely noisy audio signals captured by microphones of a hose-shaped rescue robot. To help a remote operator of such a robot pick up a weak voice of a human buried under rubble, it is crucial to suppress the loud ego-noise caused by the movements of the robot in real time. We tackle this task by using online robust principal component analysis (ORPCA) for decomposing the spectrogram of an observed noisy signal into the sum of low-rank and sparse spectrograms that are expected to correspond to periodic ego-noise and human voices. Using a microphone array distributed on the long body of a hose-shaped robot, ego-noise suppression can be further improved by combining the results of ORPCA applied to the observed signal captured by each microphone. Experiments using a 3-m hose-shaped rescue robot with eight microphones show that the proposed method improves the performance of conventional ego-noise suppression using only one microphone by 7.4 dB in SDR and 17.2 in SIR.

关键词： Rescue robots Microphone arrays Matrix decomposition Radio frequency Mobile robots

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Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

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Nature genetics 2018年第5期50卷 766-767页

作者： Valérie Turcot Yingchang Lu Heather M Highland Claudia Schurmann Anne E Justice Rebecca S Fine Jonathan P Bradfield Tõnu Esko Ayush Giri Mariaelisa Graff Xiuqing Guo Audrey E Hendricks Tugce Karaderi Adelheid Lempradl Adam E Locke Anubha Mahajan Eirini Marouli Suthesh Sivapalaratnam Kristin L Young Tamuno Alfred Mary F Feitosa Nicholas G D Masca Alisa K Manning Carolina Medina-Gomez Poorva Mudgal Maggie C Y Ng Alex P Reiner Sailaja Vedantam Sara M Willems Thomas W Winkler Gonçalo Abecasis Katja K Aben Dewan S Alam Sameer E Alharthi Matthew Allison Philippe Amouyel Folkert W Asselbergs Paul L Auer Beverley Balkau Lia E Bang Inês Barroso Lisa Bastarache Marianne Benn Sven Bergmann Lawrence F Bielak Matthias Blüher Michael Boehnke Heiner Boeing Eric Boerwinkle Carsten A Böger Jette Bork-Jensen Michiel L Bots Erwin P Bottinger Donald W Bowden Ivan Brandslund Gerome Breen Murray H Brilliant Linda Broer Marco Brumat Amber A Burt Adam S Butterworth Peter T Campbell Stefania Cappellani David J Carey Eulalia Catamo Mark J Caulfield John C Chambers Daniel I Chasman Yii-Der I Chen Rajiv Chowdhury Cramer Christensen Audrey Y Chu Massimiliano Cocca Francis S Collins James P Cook Janie Corley Jordi Corominas Galbany Amanda J Cox David S Crosslin Gabriel Cuellar-Partida Angela D'Eustacchio John Danesh Gail Davies Paul I W Bakker Mark C H Groot Renée Mutsert Ian J Deary George Dedoussis Ellen W Demerath Martin Heijer Anneke I Hollander Hester M Ruijter Joe G Dennis Josh C Denny Emanuele Di Angelantonio Fotios Drenos Mengmeng Du Marie-Pierre Dubé Alison M Dunning Douglas F Easton Todd L Edwards David Ellinghaus Patrick T Ellinor Paul Elliott Evangelos Evangelou Aliki-Eleni Farmaki I Sadaf Farooqi Jessica D Faul Sascha Fauser Shuang Feng Ele Ferrannini Jean Ferrieres Jose C Florez Ian Ford Myriam Fornage Oscar H Franco Andre Franke Paul W Franks Nele Friedrich Ruth Frikke-Schmidt Tessel E Galesloot Wei Gan Ilaria Gandin Paolo Gasparini Jane Gibson Vilmantas Giedraitis Anette P Gjesing Penny Gordon-Larsen Mathias Gorski Hans-Jörgen Montreal Heart Institute Université de Montréal Montreal Quebec Canada. Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University School of Medicine Nashville TN USA. Charles Bronfman Institute for Personalized Medicine Icahn School of Medicine at Mount Sinai New York NY USA. Genetics of Obesity and Related Metabolic Traits Program Icahn School of Medicine at Mount Sinai New York NY USA. Department of Epidemiology University of North Carolina Chapel Hill NC USA. Human Genetics Center University of Texas School of Public Health University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences University of Texas Health Science Center at Houston Houston TX USA. Broad Institute of MIT and Harvard Cambridge MA USA. Department of Genetics Harvard Medical School Boston MA USA. Division of Endocrinology and Center for Basic and Translational Obesity Research Boston Children's Hospital Boston MA USA. Center for Applied Genomics Division of Human Genetics Children's Hospital of Philadelphia Philadelphia PA USA. Quantinuum Research LLC San Diego CA USA. Estonian Genome Center University of Tartu Tartu Estonia. Division of Epidemiology Department of Medicine Institute for Medicine and Public Health Vanderbilt Genetics Institute Vanderbilt University Nashville TN USA. Institute for Translational Genomics and Population Sciences LABioMed at Harbor-UCLA Medical Center Torrance CA USA. Wellcome Trust Sanger Institute Hinxton UK. Department of Mathematical and Statistical Sciences University of Colorado Denver CO USA. Wellcome Trust Centre for Human Genetics University of Oxford Oxford UK. Department of Biological Sciences Faculty of Arts and Sciences Eastern Mediterranean University Famagusta Cyprus. Max Planck Institute of Immunobiology and Epigenetics Freiburg Germany. Department of Biostatistics and Center for Statistical Genetics University of M

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.

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Technical data analysis for movement prediction of Euro to USD using Genetic Algorithm-Neural Network

Technical data analysis for movement prediction of Euro to U...

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International Seminar on Intelligent Technology and Its Applications (ISITIA)

作者： Ary Sespajayadi Indrabayu Ingrid Nurtanio Artificial Intelligent and Multimedia Processing Research Group Makassar Indonesia Graduate of Informatics Engineering Study Programme Hasanuddin University Makassar Indonesia Informatics Engineering Study Program Hasanuddin University Makassar Indonesia Electrical Engineering Study Program Hasanuddin University Makassar Indonesia

In the foreign currency exchange (FOREX), a technical data analysis system for predicting currency movements is needed to help traders in decision making. Thus, this study proposes a system of technical data analysis to movement prediction of Euro to USD using Genetic Algorithm-Neural Network (GANN). To generate a predicted value, Genetic Algorithm searching for the best value of Feed Forward Neural Network (FFNN) trained with the Neural Network method that produced a net to predict. The Validation of predicted results with GANN method based on the degree of accuracy as follows. RMSE values of open is 0.00043; The RMSE values of high is 0.00068; The RMSE value of low is 0.00075; and RMSE values of close is 0.00070.

关键词： Genetic algorithms Biological cells Training Artificial neural networks Accuracy Prediction algorithms

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Author Correction: Discovery of stimulation-responsive immune enhancers with CRISPR activation

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Nature 2018年第7715期559卷 E13页

作者： Dimitre R Simeonov Benjamin G Gowen Mandy Boontanrart Theodore L Roth John D Gagnon Maxwell R Mumbach Ansuman T Satpathy Youjin Lee Nicolas L Bray Alice Y Chan Dmytro S Lituiev Michelle L Nguyen Rachel E Gate Meena Subramaniam Zhongmei Li Jonathan M Woo Therese Mitros Graham J Ray Gemma L Curie Nicki Naddaf Julia S Chu Hong Ma Eric Boyer Frederic Van Gool Hailiang Huang Ruize Liu Victoria R Tobin Kathrin Schumann Mark J Daly Kyle K Farh K Mark Ansel Chun J Ye William J Greenleaf Mark S Anderson Jeffrey A Bluestone Howard Y Chang Jacob E Corn Alexander Marson Biomedical Sciences Graduate Program University of California San Francisco California 94143 USA. Department of Microbiology and Immunology University of California San Francisco California 94143 USA. Diabetes Center University of California San Francisco California 94143 USA. Innovative Genomics Institute University of California Berkeley California 94720 USA. Department of Molecular and Cell Biology University of California Berkeley Berkeley California 94720 USA. Sandler Asthma Basic Research Center University of California San Francisco California 94143 USA. Center for Personal Dynamic Regulomes Stanford University School of Medicine Stanford California 94305 USA. Program in Epithelial Biology Stanford University School of Medicine Stanford California 94305 USA. Department of Genetics Stanford University School of Medicine Stanford California 94305 USA. Department of Pediatrics University of California San Francisco California 94143 USA. Department of Epidemiology and Biostatistics Department of Bioengineering and Therapeutic Sciences Institute for Human Genetics (IHG) University of California San Francisco California 94143 USA. Biological and Medical Informatics Graduate Program University of California San Francisco California 94158 USA. Broad Institute of MIT and Harvard Cambridge Massachusetts 02142 USA. Analytic and Translational Genetics Unit Massachusetts General Hospital Harvard Medical School Boston Massachusetts 02114 USA. Illumina Inc. 5200 Illumina Way San Diego California 92122 USA. Department of Applied Physics Stanford University Stanford California 94025 USA. Chan Zuckerberg Biohub San Francisco California 94158 USA. Department of Medicine University of California San Francisco California 94143 USA. Innovative Genomics Institute University of California Berkeley California 94720 USA. jcorn@berkeley.edu. Department of Molecular and Cell Biology University of California Berkeley Berkeley Californi

In this Letter, analysis of steady-state regulatory T (Treg) cell percentages from Il2ra enhancer deletion (EDEL) and wild-type (WT) mice revealed no differences between them (Extended Data Fig. 9d). This analysis included two mice whose genotypes were incorrectly assigned. Even after correction of the genotypes, no significant differences in Treg cell percentages were seen when data across experimental cohorts were averaged (as was done in Extended Data Fig. 9d). However, if we normalize the corrected data to account for variation among experimental cohorts, a subtle decrease in EDEL Treg cell percentages is revealed and, using the corrected and normalized data, we have redrawn Extended Data Fig. 9d in Supplementary Fig. 1. The Supplementary Information to this Amendment contains the corrected and reanalysed Extended Data Fig. 9d. The sentence "This enhancer deletion (EDEL) strain also had no obvious T cell phenotypes at steady state (Extended Data Fig. 9)." should read: "This enhancer deletion (EDEL) strain had a small decrease in the percentage of Treg cells (Extended Data Fig. 9).". This error does not affect any of the main figures in the Letter or the data from mice with the human autoimmune-associated single nucleotide polymorphism (SNP) knocked in or with a 12-base-pair deletion at the site (12DEL). In addition, we stated in the Methods that we observed consistent immunophenotypes of EDEL mice across three founders, but in fact, we observed consistent phenotypes in mice from two founders. This does not change any of our conclusions and the original Letter has not been corrected.

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Unintended pregnancy: a framework for prevention and options for midlife women in the US

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Women's midlife health 2017年第1期3卷 8页

作者： Versie Johnson-Mallard Elizabeth A Kostas-Polston Nancy Fugate Woods Katherine E Simmonds Ivy M Alexander Diana Taylor 1Department of Family Community and Health System Science Robert Wood Johnson Nurse Faculty Scholar Alum University of Florida College of Nursing Gainesville FL USA. 2Daniel K. Inouye Graduate School of Nursing Uniformed Services University of the Health Sciences Bethesda MD USA. 3Biobehavioral Nursing and Health Informatics Interim Associate Dean for Diversity Equity and Inclusion University of Washington School of Nursing Seattle WA USA. 4MGH Institute of Health Professions Boston MA USA. Director of Advance Practice Programs Storrs CT USA. 6UCSF School of Nursing Research Faculty Advancing New Standards in Reproductive Health Program (ANSIRH) UCSF Bixby Center for Global Reproductive Health University of California San Francisco CA USA.

Recently unintended pregnancies have been described as "a new kind of mid-life crisis." Given the high prevalence of unwanted or mistimed pregnancy in the US, we examined the sexual and reproductive health patterns of sexually active midlife women. An examination of the prevalence of unintended pregnancy among midlife women revealed a gap in data indicating unmet sexual and reproductive health needs of midlife women. The application of a framework for primary, secondary and tertiary prevention for unintended pregnancy may assist with guiding care for women and identifying implications for reproductive health policy and potential political interference as they relate to sexual and reproductive health in midlife women.

关键词： Abortion Age Contraception Framework Menopause Pregnancy Reproductive health Sex Transition Women

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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A sound-based online method for estimating the time-varying posture of a hose-shaped robot 12

A sound-based online method for estimating the time-varying ...

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12th IEEE International Symposium on Safety, Security and Rescue Robotics, SSRR 2014

作者： Bando, Yoshiaki Itoyama, Katsutoshi Konyo, Masashi Tadokoro, Satoshi Nakadai, Kazuhiro Yoshii, Kazuyoshi Okuno, Hiroshi G. Graduate School of Informatics Kyoto Univ. Kyoto606-8501 Japan Graduate School of Information Science Tohoku Univ. Miyagi980-8579 Japan Honda Research Institute Japan Co. Ltd. Saitama351-0114 Japan Graduate Program for Embodiment Informatics Waseda Univ. Tokyo169-0072 Japan

ISBN: (纸本)9781479941995

This paper presents an online method that can accurately estimate the time-varying posture of a moving hose-shaped robot having multiple microphones and loudspeakers. Sound-based posture estimation has been considered to be promising for circumventing the cumulative error problem of conventional integral-type methods using differential information obtained by inertial sensors. Our robot emits a reference signal from a loud-speaker one by one and estimates its posture by measuring the time differences of arrival (TDOAs) at the microphones. To accurately estimate the posture of the robot (the relative positions of the microphones and loudspeakers) even when the robot moves, we propose a novel state-space model that represents the dynamics of not only the posture itself but also its change rate in the state space. This model is used for predicting the current posture by using an unscented Kalman filter. The experiments using a 3m moving hose-shaped robot with eight microphones and seven loudspeakers showed that our method achieved less than 20 cm error at the tip position even after the robot moved over a long time, whereas the estimation error obtained by a conventional integral-type method increased monotonically over time. © 2014 IEEE.

关键词： Microphones

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FANTOM5 CAGE profiles of human and mouse samples

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Scientific Data 2017年第1期4卷 1-10页

作者： Noguchi, Shuhei Arakawa, Takahiro Fukuda, Shiro Furuno, Masaaki Hasegawa, Akira Hori, Fumi Ishikawa-Kato, Sachi Kaida, Kaoru Kaiho, Ai Kanamori-Katayama, Mutsumi Kawashima, Tsugumi Kojima, Miki Kubosaki, Atsutaka Manabe, Ri-Ichiroh Murata, Mitsuyoshi Nagao-Sato, Sayaka Nakazato, Kenichi Ninomiya, Noriko Nishiyori-Sueki, Hiromi Noma, Shohei Saijyo, Eri Saka, Akiko Sakai, Mizuho Simon, Christophe Suzuki, Naoko Tagami, Michihira Watanabe, Shoko Yoshida, Shigehiro Arner, Peter Axton, Richard A. Babina, Magda Kenneth Baillie, J. Barnett, Timothy C. Beckhouse, Anthony G. Blumenthal, Antje Bodega, Beatrice Bonetti, Alessandro Briggs, James Brombacher, Frank Carlisle, Ailsa J. Clevers, Hans C. Davis, Carrie A. Detmar, Michael Dohi, Taeko Edge, B. Albert S. Edinger, Matthias Ehrlund, Anna Ekwall, Karl Endoh, Mitsuhiro Enomoto, Hideki Eslami, Afsaneh Fagiolini, Michela Fairbairn, Lynsey Farach-Carson, Mary C. Faulkner, Geoffrey J. Ferrai, Carmelo Fisher, Malcolm E. Forrester, Lesley M. Fujita, Rie Furusawa, Jun-Ichi Geijtenbeek, Teunis B. Gingeras, Thomas Goldowitz, Daniel Guhl, Sven Guler, Reto Gustincich, Stefano Ha, Thomas J. Hamaguchi, Masahide Hara, Mitsuko Hasegawa, Yuki Herlyn, Meenhard Heutink, Peter Hitchens, Kelly J. Hume, David A. Ikawa, Tomokatsu Ishizu, Yuri Kai, Chieko Kawamoto, Hiroshi Kawamura, Yuki I. Kempfle, Judith S. Kenna, Tony J. Kere, Juha Khachigian, Levon M. Kitamura, Toshio Klein, Sarah Peter Klinken, S. Knox, Alan J. Kojima, Soichi Koseki, Haruhiko Koyasu, Shigeo Lee, Weonju Lennartsson, Andreas MacKay-Sim, Alan Mejhert, Niklas Mizuno, Yosuke Morikawa, Hiromasa Morimoto, Mitsuru Moro, Kazuyo Morris, Kelly J. Motohashi, Hozumi Mummery, Christine L. Nakachi, Yutaka Nakahara, Fumio Nakamura, Toshiyuki Nakamura, Yukio Nozaki, Tadasuke Ogishima, Soichi Ohkura, Naganari Ohno, Hiroshi Ohshima, Mitsuhiro Okada-Hatakeyama, Mariko Okazaki, Yasushi Orlando, Valerio Ovchinnikov, Dmitry A. Passier, Robert Patrikakis, Margaret Pombo, Ana Pradhan-Bhatt, Swati Qin, Xian-Yang Rehli, Michael Rizzu, Patrizia Roy, S Division of Genomic Technologies RIKEN Center for Life Science Technologies Yokohama Kanagawa 230-0045 Japan RIKEN Omics Science Center Yokohama Kanagawa 230-0045 Japan Department of Medicine Karolinska Institutet Stockholm 14186 Sweden Karolinska University Hospital Center for Metabolism and Endocrinology Stockholm 14186 Sweden Scottish Centre for Regenerative Medicine University of Edinburgh 5 Little France Drive Edinburgh EH164UU United Kingdom Department of Dermatology and Allergy Charite University Medicine Berlin Charitéplatz 1 Berlin 10117 Germany Roslin Institute and Royal School of Veterinary Studies University of Edinburgh Edinburgh EH259RG United Kingdom Australian Infectious Diseases Research Centre University of Queensland St Lucia 4072 QLD Australia School of Chemistry and Molecular Biosciences University of Queensland St Lucia 4072 QLD Australia Bio-Rad Laboratories Pty Ltd Hercules 94547 CA United States University of Queensland Diamantina Institute University of Queensland Woolloongabba 4102 QLD Australia IRCCS Fondazione Santa Lucia Via del Fosso di Fiorano 64 Rome 00143 Italy Australian Institute for Bioengineering and Nanotechnology University of Queensland Brisbane St Lucia 4072 QLD Australia Division of Immunology Institute of Infectious Diseases and Molecular Medicine University of Cape Town Anzio Road Observatory 7925 South Africa Immunology of Infectious Diseases Faculty of Health Sciences South African Medical Research Council University of Cape Town Anzio Road 7925 South Africa International Centre for Genetic Engineering and Biotechnology Cape Town Component Anzio Road 7925 South Africa Hubrecht Institute Royal Netherlands Academy of Arts and Sciences Uppsalalaan 8 3584 Netherlands University Medical Centre Utrecht Postbus 85500 Utrecht 3508 Netherlands Genomics Cold Spring Harbor Laboratory Cold Spring Harbor New York 11797 NY United States Institute of Pharmaceutical Sciences ETH Zurich Vladi

In the FANTOM5 project, transcription initiation events across the human and mouse genomes were mapped at a single base-pair resolution and their frequencies were monitored by CAGE (Cap Analysis of Gene Expression) coupled with single-molecule sequencing. Approximately three thousands of samples, consisting of a variety of primary cells, tissues, cell lines, and time series samples during cell activation and development, were subjected to a uniform pipeline of CAGE data production. The analysis pipeline started by measuring RNA extracts to assess their quality, and continued to CAGE library production by using a robotic or a manual workflow, single molecule sequencing, and computational processing to generate frequencies of transcription initiation. Resulting data represents the consequence of transcriptional regulation in each analyzed state of mammalian cells. Non-overlapping peaks over the CAGE profiles, approximately 200,000 and 150,000 peaks for the human and mouse genomes, were identified and annotated to provide precise location of known promoters as well as novel ones, and to quantify their activities.

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