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Proceedings of the 16th Annual UT-KBRIN Bioinformatics Summit 2016: bioinformatics

BMC Bioinformatics 2017年第9期18卷 1-9页

作者： Eric C. Rouchka Juw Won Park Julia H. Chariker David A. Tieri Shreedharkumar Rajurkar Vikas Singh Nishchal K. Verma Yan Cui Mark Farman Bradford Condon Jolanta Jaromczyk Neil Moore Jerzy Jaromczyk Daniel Harris Patrick Calie Eun Kyong Shin Robert L. Davis Arash Shaban-Nejad Joshua M. Mitchell Hunter N. B. Moseley Robert M. Flight Qing Jun Wang Richard M. Higashi Teresa W-M Fan Andrew N. Lane Liangqun Lu Bernie J Daigle Jr. Xi Chen Andrey Smelter Jerzy W. Jaromczyk Bailey K. Phan Nathaniel J. Serpico Ethan G. Toney Li Chen Caroline E. Melton Jennifer R. Mandel Bernie J. Daigle Jr. Hao Chen Kazi I. Zaman Ramin Homayouni Patrick J. Trainor Andrew P. DeFilippis Samantha M. Carlisle Shesh N. Rai Department of Computer Engineering and Computer Science University of Louisville Duthie Center for Engineering Louisville KY 40292 USA Kentucky Biomedical Research Infrastructure (KBRIN) Bioinformatics Core 522 East Gray Street Louisville KY 40292 USA Department of Psychological and Brain Sciences University of Louisville Louisville KY 40292 USA Department of Anatomical Sciences and Neurobiology University of Louisville Louisville KY 40292 USA Department of Electrical Engineering IIT Kanpur India Department of Microbiology Immunology and Biochemistry University of Tennessee Health Science Center Memphis TN 38103 USA Center for Integrative and Translational Genomics University of Tennessee Health Science Center Memphis TN 38103 USA Department of Plant Pathology University of Kentucky Lexington KY 40546 USA UK Healthcare Genomics University of Kentucky Lexington KY 40536 USA Department of Entomology & Plant Pathology University of Tennessee Knoxville TN 37996 USA Department of Forestry University of Kentucky Lexington KY 40506 USA Department of Computer Science University of Kentucky Lexington KY 40506 USA Department of Computer Science University of Kentucky Lexington KY 40508 USA Department of Biological Sciences Eastern Kentucky University Richmond KY 40475 USA University of Tennessee Health Science Center – Oak-Ridge National Lab (UTHSC-ORNL) Center for Biomedical Informatics Department of Pediatrics Memphis TN 38103 USA Department of Molecular & Cellular Biochemistry University of Kentucky Lexington KY 40536 USA Markey Cancer Center University of Kentucky Lexington KY 40536 USA Center for Environmental and Systems Biochemistry University of Kentucky Lexington KY 40536 USA Institute for Biomedical Informatics University of Kentucky Lexington KY 40536 USA Department of Molecular and Cellular Biochemistry University of Kentucky Lexington KY 40536 USA Department of Statistics University of Kentucky Louisville KY

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The ABCs of Experimental Evolution

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International Scholarly Research Notices 2013年第1期2013卷

作者： Zaid Abdo Mathew Stein Andrzej Wojtowicz Kim M. Pepin Departments of Statistics University of Idaho Moscow ID 83844 USAuidaho.edu Department of Mathematics University of Idaho Moscow ID 83844 USAuidaho.edu Program of Bioinformatics and Computational Biology (BCB) University of Idaho Moscow ID 83844 USAuidaho.edu USDA-ARS South Atlantic Area 950 College Station Road Athens GA 30605-2720 USA Department of Computer Engineering University of Idaho Moscow ID 83844 USAuidaho.edu Micron Technology Inc. Boise ID 83716 *** Department of Animal Sciences Washington State University Pullman WA 99164 USAwsu.edu Fogarty International Center National Institutes of Health 31 Center Drive MSC 2220 Bethesda MD 20892-2220 USAfic.nih.gov Department of Biology Colorado State University Campus Delivery 1878 Fort Collins CO 80523 USAcolostate.edu

Microbial evolution is complex and is influenced by many sources of variation. Experimental evolution is no exception, although it is more controlled, easily replicated, and typically devoid of interactions between species. Mathematical modeling of the evolutionary process can help in understanding the underlying mechanisms that drive outcome of such experiments. These models can be complex and parameter rich, limiting their feasibility for statistical inference. In this paper, we introduce the use of Approximate Bayesian Computation (ABC) as a tool for statistical inference in the study of experimental evolution. ABC is a fast and simple method for fitting complex models to data. We utilize this method, coupled with a mechanistic model of experimental evolution, to study the evolution process of bacteriophage ϕ X174 under benign selection pressure. Our results highlight three mutation-selection scenarios that could explain this process: high mutation/low selection pressure, low mutation/high selection pressure, and low mutation/low selection pressure, with posterior support of 19%, 9.5%, and 71.5% for each of these scenarios, respectively. Sequence data support the first candidate. Though surprising, this scenario was not improbable based on our analysis.

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Methods for Evaluating Medical Tests and Biomarkers

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Diagnostic and Prognostic Research 2017年第1期1卷 1-34页

作者： Gowri Gopalakrishna Miranda Langendam Patrick Bossuyt Mariska Leeflang Rob Scholten Anna Noel-Storr James Thomas Iain Marshall Byron Wallace Penny Whiting Clare Davenport Gowri GopalaKrishna Isabel de Salis Sue Mallett Robert Wolff Marie Westwood Jos Kleinen Richard Riley Gary Collins Hans Reitsma Karel Moons Antonia Zapf Katharina Kramer Annika Hoyer Oliver Kuss J. Ensor R. D. Riley J. J. Deeks E. C. Martin Gerta Rücker Martin Schumacher Susanne Steinhauser Joie Ensor Kym Snell Brian Willis Jon Deeks Thomas Debray Lavinia Ferrante di Ruffano Sian Taylor-Phillips Chris Hyde Stuart A. Taylor Gauraang Batnagar Lavinia Ferrante Di Ruffano Farah Seedat Aileen Clarke Sarah Byron Frances Nixon Rebecca Albrow Thomas Walker Carla Deakin Zhivko Zhelev Harriet Hunt Yaling Yang Lucy Abel James Buchanan Thomas Fanshawe Bethany Shinkins Laure Wynants Sabine Van Huffel Jan Verbakel Dirk Timmerman Ben Van Calster Aeliko Zwinderman Jason Oke Jack O’Sullivan Rafael Perera Brian Nicholson Hannah L. Bromley Tracy E. Roberts Adele Francis Denniis Petrie G. Bruce Mann Kinga Malottki Holly Smith Lucinda Billingham Alice Sitch Oke Gerke Mie Holm-Vilstrup Eivind Antonsen Segtnan Ulrich Halekoh Poul Flemming Høilund-Carlsen Bernard G. Francq Jac Dinnes Julie Parkes Walter Gregory Jenny Hewison Peter Selby Doug Altman William Rosenberg Julien Asselineau Paul Perez Aïssatou Paye Emilie Bessede Cécile Proust-Lima Christiana Naaktgeboren Joris de Groot Johannes Reitsma Anne Rutjes Emmanuel Ogundimu Jonathan Cook Yannick Le Manach Yvonne Vergouwe Romin Pajouheshnia Rolf Groenwold Karen Moons Linda Peelen Bavo De Cock Daan Nieboer Ewout W. Steyerberg Micael J. Pencina Jennifer Cooper Nick Parsons Chris Stinton Steve Smith Andy Dickens Rachel Jordan Alexandra Enocson David Fitzmaurice Peymane Adab Charles Boachie Gaj Vidmar Karoline Freeman Martin Connock Rachel Court Carl Moons Jessica Harris Zoe Plummer Barnaby Reeves Chris Rogers Andrew Mumford Kurtis Lee Veerle Verheyden Gianni D. Angelini Gavin J. Murphy Jeremy Huddy Melody Ni George Hanna Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands Department of Clinical Epidemiology and Biostatistics Academic Medical Center University of Amsterdam Amsterdam Netherlands Cochrane Netherlands Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht Netherlands Cochrane Dementia and Cognitive Improvement Group University of Oxford Oxford UK EPPI-Centre Department of Social Science University College London London UK Division of Health and Social Care Research King’s College London London UK College of Computer and Information Science Northeastern University Boston USA University Hospitals Bristol NHS Foundation Trust School of Social and Community Medicine Bristol UK Institute of Applied Health Research University of Birmingham Birmingham UK School of Social and Community Medicine University of Bristol Bristol UK Kleijnen Systematic Reviews Ltd York UK Research Institute for Primary Care and Health Sciences Keele University Keele UK Centre for Statistics in Medicine Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences University of Oxford Oxford UK Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht The Netherlands Cochrane Netherlands University Medical Center Utrecht Utrecht The Netherlands Julius Center for Health Sciences and Primary Care University Medical Center Utrecht 3584 CG Utrecht Netherlands Department of Medical Statistics University Medical Center Göttingen Göttingen Germany Institute for Biometry and Epidemiology German Diabetes Center Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf Germany Manchester Pharmacy School University of Manchester Manchester UK Institute for Medical Biometry and Statistics Faculty of Medicine and Medical Center – University of Freiburg Stefan-Meier-Str. 26 79104 Freiburg Germany

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Correction to: Culture of mesenchymal stem cells derived from equine synovial membrane in alginate hydrogel microcapsules

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Stem cell research & therapy 2018年第1期9卷 259页

作者： Vitor Hugo Santos João Pedro Hübbe Pfeifer Jaqueline Brandão de Souza Betsabéia Heloisa Gentilha Milani Rogério Antonio de Oliveira Marjorie Golim Assis Elenice Deffune Andrei Moroz Ana Liz Garcia Alves Department of Veterinary Surgery and Anesthesiology University of Veterinary Medicine and Animal Science UNESP District of Rubião Júnior s / n Botucatu São Paulo Brazil. Departament of Statistics Institute of Biosciences UNESP District of Rubião Júnior s / n Botucatu SP Brazil. Departament of Graduate Program in Research and Development Medical Biotechnology UNESP Blood Centre Division District of Rubião Júnior s / n Botucatu SP Brazil. Departament of Urology Blood Centre Division - Laboratory of Cellular Engineering University of Medicine UNESP District of Rubião Junior s / n Botucatu SP Brazil. Departament of Bioprocesses and Biotechnology FCFAR - UNESP Rodovia Araraquara Jaú KM 01 São Paulo Brazil. Department of Veterinary Surgery and Anesthesiology University of Veterinary Medicine and Animal Science UNESP District of Rubião Júnior s / n Botucatu São Paulo Brazil. anaalves@fmvz.unesp.br.

The original article [1] contained a minor error regarding the mean diameter of the alginate microcapsules described in relation to Fig. 4 in the Results section. The microcapsules had an actual mean diameter of ...

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Quantum computing at the frontiers of biological sciences

arXiv

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arXiv 2019年

作者： Emani, Prashant S. Warrell, Jonathan Anticevic, Alan Bekiranov, Stefan Gandal, Michael McConnell, Michael J. Sapiro, Guillermo Aspuru-Guzik, Alán Baker, Justin Bastiani, Matteo McClure, Patrick Murray, John Sotiropoulos, Stamatios N. Taylor, Jacob Senthil, Geetha Lehner, Thomas Gerstein, Mark B. Harrow, Aram W. Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Department of Molecular Biophysics and Biochemistry Yale University New HavenCT06520 United States Yale School of Medicine Department of Psychiatry New HavenCT06511 United States University of Virginia School of Medicine Department of Biochemistry and Molecular Genetics CharlottesvilleVA22903 United States Department of Psychiatry Semel Institute David Geffen School of Medicine University of California–Los Angeles 695 Charles E. Young Drive South Los AngelesCA90095 United States Univ. of Virginia School of Medicine Department of Neuroscience CharlottesvilleVA22903 United States Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States Department of Chemistry University of Toronto 80 St. George Street TorontoONM5S 3H6 Canada TorontoONM5S 1M1 Canada CIFAR Artificial Intelligence Research Chair Vector Institute TorontoONM5S 1M1 Canada Department of Computer Science University of Toronto 40 St. George Street TorontoONM5S 2E4 Canada Schizophrenia and Bipolar Disorder Program McLean Hospital BelmontMA02478 United States Department of Psychiatry Harvard Medical School BostonMA02114 United States Sir Peter Mansfield Imaging Centre School of Medicine University of Nottingham NottinghamNG7 2RD United Kingdom Machine Learning Team National Institute of Mental Health BethesdaMD20892 United States Section on Functional Imaging Methods National Institute of Mental Health BethesdaMD20892 United States Department of Psychiatry Yale University School of Medicine New HavenCT06511 United States Department of Physics Yale University New HavenCT06511 United States Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD20742 United States National Institute of Standards and Technology GaithersburgMD20899 United States Office of Genomics Research Coordination N

The search for meaningful structure in biological data has relied on cutting-edge advances in computational technology and data science methods. However, challenges arise as we push the limits of scale and complexity in biological problems. Innovation in massively parallel, classical computing hardware and algorithms continues to address many of these challenges, but there is a need to simultaneously consider new paradigms to circumvent current barriers to processing speed. Accordingly, we articulate a view towards quantum computation and quantum information science, where algorithms have demonstrated potential polynomial and exponential computational speedups in certain applications, such as machine learning. The maturation of the field of quantum computing, in hardware and algorithm development, also coincides with the growth of several collaborative efforts to address questions across length and time scales, and scientific disciplines. We use this coincidence to explore the potential for quantum computing to aid in one such endeavor: the merging of insights from genetics, genomics, neuroimaging and behavioral phenotyping. By examining joint opportunities for computational innovation across fields, we highlight the need for a common language between biological data analysis and quantum computing. Ultimately, we consider current and future prospects for the employment of quantum computing algorithms in the biological sciences. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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Correction to: Does CO2 emissions-economic growth relationship reveal EKC in developing countries? Evidence from Kazakhstan

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Environmental science and pollution research international 2019年第34期26卷 35282页

作者： Fakhri J Hasanov Jeyhun I Mikayilov Shahriyar Mukhtarov Elchin Suleymanov King Abdullah Petroleum Studies and Research Center P.O. Box 88550 Riyadh 11672 Saudi Arabia. Research Program on Forecasting Economics Department The George Washington University 2115 G Street NW Washington DC 20052 USA. Institute of Control Systems B. Vahabzade Street 9 AZ1141 Baku Azerbaijan. Department of Statistics and Econometrics Azerbaijan State University of Economics Istiqlaliyyat Str. 6 AZ1001 Baku Azerbaijan. Institute for Scientific Research on Economic Reforms 88a Hasan Bey Zardabi Avenue AZ1011 Baku Azerbaijan. Department ofWorld Economy Baku Engineering University Hasan Aliyev 120 AZ0101 Khirdalan Azerbaijan. smuxtarov@beu.edu.az. UNEC Empirical Research Center Azerbaijan State University of Economics (UNEC) Istiqlaliyyat Str. 6 AZ1141 Baku Azerbaijan. smuxtarov@beu.edu.az. Department of Finance Baku Engineering University Hasan Aliyev 120 AZ0101 Khirdalan Azerbaijan. The Institute of Economics Azerbaijan National Academy of Sciences H. Javid pr. 115 AZ1001 Baku Azerbaijan.

The article Does CO emissions-economic growth relationship reveal EKC in developing countries? Evidence from Kazakhstan, written by Fakhri J. Hasanov, Jeyhun I.

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Nitrogen and phosphorus constrain the CO2 fertilization of global plant biomass (vol 21, pg 561, 2020)

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NATURE CLIMATE CHANGE 2020年第7期10卷 696-697页

作者： Terrer, Cesar Jackson, Robert B. Prentice, I. Colin Keenan, Trevor F. Kaiser, Christina Vicca, Sara Fisher, Joshua B. Reich, Peter B. Stocker, Benjamin D. Hungate, Bruce A. Penuelas, Josep McCallum, Ian Soudzilovskaia, Nadejda A. Cernusak, Lucas A. Talhelm, Alan F. Van Sundert, Kevin Piao, Shilong Newton, Paul C. D. Hovenden, Mark J. Blumenthal, Dana M. Liu, Yi Y. Mueller, Christoph Winter, Klaus Field, Christopher B. Viechtbauer, Wolfgang Van Lissa, Caspar J. Hoosbeek, Marcel R. Watanabe, Makoto Koike, Takayoshi Leshyk, Victor O. Polley, H. Wayne Franklin, Oskar Department of Earth System Science Stanford University Stanford USA Institut de Ciència i Tecnologia Ambientals Universitat Autònoma de Barcelona Barcelona Spain Ecosystems Services and Management Program International Institute for Applied Systems Analysis Laxenburg Austria Woods Institute for the Environment and Precourt Institute for Energy Stanford University Stanford USA AXA Chair Programme in Biosphere and Climate Impacts Department of Life Sciences Imperial College London Silwood Park Campus Ascot UK Department of Biological Sciences Macquarie University North Ryde Australia Department of Earth System Science Tsinghua University Beijing China Department of Environmental Science Policy and Management UC Berkeley Berkeley USA Climate and Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley USA Department of Microbiology and Ecosystem Science Division of Terrestrial Ecosystem Research Faculty of Life Sciences University of Vienna Vienna Austria Evolution and Ecology Program International Institute for Applied Systems Analysis Laxenburg Austria Centre of Excellence PLECO (Plants and Ecosystems) Biology Department University of Antwerp Wilrijk Belgium Jet Propulsion Laboratory California Institute of Technology Pasadena USA Joint Institute for Regional Earth System Science and Engineering University of California at Los Angeles Los Angeles USA Department of Forest Resources University of Minnesota St. Paul USA Hawkesbury Institute for the Environment Western Sydney University Penrith Australia CREAF Cerdanyola del Vallès Spain Center for Ecosystem Science and Society Northern Arizona University Flagstaff USA Department of Biological Sciences Northern Arizona University Flagstaff USA CSIC Global Ecology Unit CREAF-CEAB-UAB Bellaterra Spain Environmental Biology Department Institute of Environmental Sciences Leiden University Leiden the Netherlands College of Marine and Environmental Sciences James Cook University Cairns

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Automatic Extraction of Medication Mentions from Tweets-Overview of the BioCreative VII Shared Task 3 Competition

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Database : the journal of biological databases and curation 2023年第2023期2023卷 baac108页

作者： Davy Weissenbacher Karen O'Connor Siddharth Rawal Yu Zhang Richard Tzong-Han Tsai Timothy Miller Dongfang Xu Carol Anderson Bo Liu Qing Han Jinfeng Zhang Igor Kulev Berkay Köprü Raul Rodriguez-Esteban Elif Ozkirimli Ammer Ayach Roland Roller Stephen Piccolo Peijin Han V G Vinod Vydiswaran Ramya Tekumalla Juan M Banda Parsa Bagherzadeh Sabine Bergler João F Silva Tiago Almeida Paloma Martinez Renzo Rivera-Zavala Chen-Kai Wang Hong-Jie Dai Luis Alberto Robles Hernandez Graciela Gonzalez-Hernandez Department of Computational Biomedicine Cedars-Sinai Medical Center Los Angeles CA USA. DBEI The Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Computer Science and Information Engineering National Central University No. 300 Zhongda Rd Zhongli District Taoyuan 320 Taiwan. IoX Center National Taiwan University Da'an District Section 4 Roosevelt Rd No. 1 Barry Lam Hall Taipei 106 Taiwan. Research Center for Humanities and Social Sciences Academia Sinica No. 128 Section 2 Academia Rd Nangang District Taipei 115 Taiwan. Computational Health Informatics Program Boston Children's Hospital Boston MA USA. Department of Pediatrics Harvard Medical School Boston MA USA. NVIDIA Santa Clara CA USA. Department of Statistics Florida State University Tallahassee FL USA. Data and Analytics Chapter F. Hoffmann-La Roche Ltd Switzerland. Pharmaceutical Research and Early Development Roche Innovation Center Basel Switzerland. Speech and Language Technology Lab DFKI Berlin Germany. Department of Biology Brigham Young University Provo UT USA. Department of Computational Medicine and Bioinformatics Medical School University of Michigan Ann Arbor MI USA. Department of Learning Health Sciences Medical School University of Michigan Ann Arbor MI USA. School of Information University of Michigan Ann Arbor MI USA. Department of Computer Science Georgia State University Atlanta GA USA. CLaC Labs Concordia University Montreal Canada. DETI Institute of Electronics and Informatics Engineering of Aveiro University of Aveiro Portugal. Department of Computation University of A Coruña Spain. Computer Science and Engineering Department Universidad Carlos III de Madrid Madrid Spain. Big Data Laboratory Chunghwa Telecom Laboratories Taoyuan Taiwan. Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan. Department of Electrical Engineering College of Electrical Engineering and Computer Sci

This study presents the outcomes of the shared task competition BioCreative VII (Task 3) focusing on the extraction of medication names from a Twitter user's publicly available tweets (the user's 'timeline'). In general, detecting health-related tweets is notoriously challenging for natural language processing tools. The main challenge, aside from the informality of the language used, is that people tweet about any and all topics, and most of their tweets are not related to health. Thus, finding those tweets in a user's timeline that mention specific health-related concepts such as medications requires addressing extreme imbalance. Task 3 called for detecting tweets in a user's timeline that mentions a medication name and, for each detected mention, extracting its span. The organizers made available a corpus consisting of 182 049 tweets publicly posted by 212 Twitter users with all medication mentions manually annotated. The corpus exhibits the natural distribution of positive tweets, with only 442 tweets (0.2%) mentioning a medication. This task was an opportunity for participants to evaluate methods that are robust to class imbalance beyond the simple lexical match. A total of 65 teams registered, and 16 teams submitted a system run. This study summarizes the corpus created by the organizers and the approaches taken by the participating teams for this challenge. The corpus is freely available at https://***/tasks/biocreative-vii/track-3/. The methods and the results of the competing systems are analyzed with a focus on the approaches taken for learning from class-imbalanced data.

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Genome-wide association study of long COVID

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Nature Genetics 2025年 1-16页

作者： Vilma Lammi Tomoko Nakanishi Samuel E. Jones Juha Karjalainen Martin Broberg Hele H. Haapaniemi Matti Pirinen Mari E. K. Niemi Mattia Cordioli Mark J. Daly Andrea Ganna Hanna M. Ollila J. Brent Richards Yukinori Okada Shea J. Andrews Beatriz Cortés Rafael de Cid Susana Iraola-Guzmán Natalia Blay Xavier Farré Heath E. O’Brien Thompson Hannah Patrick J. Short Ana Ochoa-Guzman Michelle Duran-Gomez Brian E. Fulton-Howard Masahiro Kanai Axel Schmidt Daniella Balla Julia Heggemann Sonja Schultz Pari Behzad Markus M. Nöthen Abigail Miller Kerstin U. Ludwig Ruth E. Mitchell George Davey Smith Nicholas J. Timpson Abdou Mousas Evangelos Evangelou Evangelia Ntzani Konstantinos K. Tsilidis Massimo Mangino Alicia Huerta-Chagoya Nasa Sinnott-Armstrong Elizabeth T. Cirulli Francisco Tanudjaja Efren Sandoval Nicole L. Washington Simon White Alexandre Bolze Kelly M. Schiabor Barrett Marc Vaudel Alex S. F. Kwong Amit K. Maiti Minttu M. Marttila Daniel C. Posner Alexis A. Rodriguez Chiara Batini Beatriz Guillen-Guio Olivia C. Leavy Anna L. Guyatt Catherine John Louise V. Wain Francesca Minnai Anna R. Dearman Benedict Hignell Meena Kumari C. A. Robert Warmerdam Lude H. Franke Celia B. Sequeros Søren Brunak David Westergaard Karina Banasik Thomas W. Winkler Iris M. Heid Daniel M. Jordan Ryan C. Thompson Alexander W. Charney Laura G. Sloofman Nicole W. Simons Noam D. Beckmann Raimonds Rešcenko Vita Rovite Peculis Raitis Monta Briviba Janis Klovinš Laura Ansone Lorenzo Miano Flora Peyvandi Francesco Malvestiti Nicola Montano Alessandra Bandera Francesco Bruno Arturo Blasi Jacqueline M. Lane Jakob M. Cherry Ryan K. Chung Laura Carvajal-Silva Kevin Aguilar-Valdés Leslie C. Cerpa Tamara V. Arévalo Eduardo Lamoza Alicia Colombo Ricardo A. Verdugo Erika Frangione Xu Xinyi Jennifer Taher Jordan Lerner-Ellis Lindsay Guare Shefali S. Verma Ekaterina Vergasova Michil Trofimov Layal Shaheen Nikolay Plotnikov Anna Kim Dmitrii Kharitonov Alexei Kamelin Alexander Rakitko Eirini Marouli Pasquale Striano Ummu Afeera Zainulabid Ashutosh Kumar Hajar Fa Institute for Molecular Medicine Finland (FIMM) Helsinki Institute of Life Science (HiLIFE) University of Helsinki Helsinki Finland Department of Human Genetics McGill University Montreal Quebec Canada Centre for Clinical Epidemiology Department of Medicine Lady Davis Institute Jewish General Hospital McGill University Montreal Quebec Canada Kyoto-McGill International Collaborative Program in Genomic Medicine Graduate School of Medicine Kyoto University Kyoto Japan Department of Genome Informatics Graduate School of Medicine the University of Tokyo Tokyo Japan Research Fellow Japan Society for the Promotion of Science Tokyo Japan Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA Stanley Center for Psychiatric Research Broad Institute of Harvard and MIT Cambridge MA USA Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Department of Mathematics and Statistics University of Helsinki Helsinki Finland Department of Public Health University of Helsinki Helsinki Finland Broad Institute Cambridge MA USA Analytical and Translational Genetics Unit Massachusetts General Hospital Harvard Medical School Boston MA USA Center for Genomic Medicine Massachusetts General Hospital Boston MA USA Anesthesia Critical Care and Pain Medicine Massachusetts General Hospital and Harvard Medical School Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Twin Research King’s College London London UK 5 Prime Sciences Inc Montreal Quebec Canada Department of Epidemiology Biostatistics and Occupational Health McGill University Montreal Quebec Canada Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan Laboratory for Systems Genetics RIKEN Center for Integrative Medical Sciences Yokohama Japan Laboratory of Statistical Immunology Immunology Frontier Research Center (WPI-IFReC) Osaka University Suita Japan Departmen

Infections can lead to persistent symptoms and diseases such as shingles after varicella zoster or rheumatic fever after streptococcal infections. Similarly, severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) infection can result in long coronavirus disease (COVID), typically manifesting as fatigue, pulmonary symptoms and cognitive dysfunction. The biological mechanisms behind long COVID remain unclear. We performed a genome-wide association study for long COVID including up to 6,450 long COVID cases and 1,093,995 population controls from 24 studies across 16 countries. We discovered an association ofFOXP4with long COVID, independent of its previously identified association with severe COVID-19. The signal was replicated in 9,500 long COVID cases and 798,835 population controls. Given the transcription factor FOXP4’s role in lung physiology and pathology, our findings highlight the importance of lung function in the pathophysiology of long COVID.

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