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Reproducible brain-wide association studies require thousands of individuals (Mar, 10.1038/s41586-022-04492-9, 2022)

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NATURE 2022年第7911期605卷 E11-E11页

作者： Marek, Scott Tervo-Clemmens, Brenden Calabro, Finnegan J. Montez, David F. Kay, Benjamin P. Hatoum, Alexander S. Donohue, Meghan Rose Foran, William Miller, Ryland L. Hendrickson, Timothy J. Malone, Stephen M. Kandala, Sridhar Feczko, Eric Miranda-Dominguez, Oscar Graham, Alice M. Earl, Eric A. Perrone, Anders J. Cordova, Michaela Doyle, Olivia Moore, Lucille A. Conan, Gregory M. Uriarte, Johnny Snider, Kathy Lynch, Benjamin J. Wilgenbusch, James C. Pengo, Thomas Tam, Angela Chen, Jianzhong Newbold, Dillan J. Zheng, Annie Seider, Nicole A. Van, Andrew N. Metoki, Athanasia Chauvin, Roselyne J. Laumann, Timothy O. Greene, Deanna J. Petersen, Steven E. Garavan, Hugh Thompson, Wesley K. Nichols, Thomas E. Yeo, B. T. Thomas Barch, Deanna M. Luna, Beatriz Fair, Damien A. Dosenbach, Nico U. F. Department of Psychiatry Washington University School of Medicine St Louis MO USA Department of Neurology Washington University School of Medicine St Louis MO USA Department of Psychological and Brain Sciences Washington University in St Louis St Louis MO USA Department of Psychiatry Massachusetts General Hospital Harvard Medical School Boston MA USA Department of Psychology University of Pittsburgh Pittsburgh PA USA Department of Psychiatry University of Pittsburgh Pittsburgh PA USA Department of Bioengineering University of Pittsburgh Pittsburgh PA USA Department of Biomedical Engineering Washington University in St Louis St Louis MO USA Department of Radiology Washington University School of Medicine St Louis MO USA Department of Neurological Surgery Washington University School of Medicine St Louis MO USA Program in Occupational Therapy Washington University School of Medicine St Louis MO USA Department of Pediatrics Washington University School of Medicine St Louis MO USA University of Minnesota Informatics Institute University of Minnesota Minneapolis MN USA Department of Psychology University of Minnesota Minneapolis MN USA Masonic Institute for the Developing Brain University of Minnesota Medical School Minneapolis MN USA Department of Pediatrics University of Minnesota Medical School Minneapolis MN USA Department of Psychiatry Oregon Health and Science University Portland OR USA Minnesota Supercomputing Institute University of Minnesota Minneapolis MN USA Institute of Child Development University of Minnesota Medical School Minneapolis MN USA Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore Centre for Sleep and Cognition National University of Singapore Singapore Singapore Centre for Translational MR Research National University of Singapore Singapore Singapore N.1 Institute for Health Institute for Digital Medicine National University of Singapore Singapore Sing

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AN ADVANCED METHODOLOGY FOR PRELIMINARY HULL FORM DEVELOPMENT

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NAVAL ENGINEERS JOURNAL 1984年第4期96卷 147-161页

作者： LIN, WC DAY, WG HOUGH, JJ KEANE, RG WALDEN, DA KOH, IY Wen-Chin Lin:heads the Ship Powering Division at the David Taylor Naval Ship R&D Center (DTNSRDC). Dr. Lin received his B.S. degree in mechanical engineering from the National Taiwan University in 1957. He was awarded his M.S. degree in naval architecture and Ph.D. in engineering science from the University of California at Berkeley in 1963 and 1966 respectively. From 1966 to 1969 he was employed by ESSO Research and Engineering Company to conduct marine hydrodynamic research for oil tankers and offshore structures. Since joining DTNSRDC in 1969 he has actively conducted and directed hydrodynamic research to advance naval ship design technology and improve ship performance. Active in national and international symposia on ship hydrodynamic research he is recognized for contributions to the ship research community. For the past six years he has been a member of the Performance Committee of the ITTC and currently serves as secretary of the committee. He is a member of SNAME and the Society of Naval Architects of Japan. William G. Day Jr:. has been employed as a naval architect at the David Taylor Naval Ship R&D Center since receiving a B.E.S. degree from the Johns Hopkins University in 1966. He obtained an M.S. E. degree from George Washington University in 1971. As Head Design Evaluation Branch of the Ship Performance Department he is responsible for model experiments to evaluate the hydrodynamic performance of ships and propulsors. He is a member of ASNE and SNAME. In-Young Koh:received his B.S. and M.S. degrees in electrical engineering from Lowell University in 1969 and 1971 respectively and his Ph.D. in applied mechanics from Rensselaer Polytechnic Institute in 1976. Dr. Koh joined DTNSRDC as an electronic engineer specializing in the application of advanced instrumentation and computer techniques to ship research and design. He is currently engaged in research and development of active control systems for naval ship applications. Dr. Koh is a member of ASNE SNAME and IEEE. David Andrew Walden:is

A ship design methodology is presented for developing hull forms that attain improved performance in both seakeeping and resistance. Contrary to traditional practice, the methodology starts with developing a seakeeping-optimized hull form without making concessions to other performance considerations, such as resistance. The seakeeping-optimized hull is then modified to improve other performance characteristics without degrading the seakeeping. Presented is a point-design example produced by this methodology. Merits of the methodology and the point design are assessed on the basis of theoretical calculations and model experiments. This methodology is an integral part of the Hull Form Design System (HFDS) being developed for computer-supported naval ship design. The modularized character of HFDS and its application to hull form development are discussed.

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THE UNITED STATES NAVY'S “DESIGN WORK STUDY” APPROACH TO THE DEVELOPMENT OF SHIPBOARD CONTROL SYSTEMS

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Naval Engineers Journal 1976年第6期88卷 62-74页

作者： PLATO, ARTIS I. GAMBREL, WILLIAM DAVID Artis I. Plato:is Head of the Design Work Study/ Shipboard Manning/Human Factors Engineering Section Systems Engineering and Analysis Branch Naval Ship Engineering Center (NAVSEC). He graduated from the City College of New York in 1956 receiving his Bachelor of Mechanical Engineering degree. Following this he started work at the New York Naval Shipyard in the Internal Combustion Engine and Cargo Elevator Section. During 1957 and 1958 he was called up for active duty with the U.S. Army Corps of Engineers and served in Europe with a Construction Engineer Battalion. After release from active duty he returned to the shipyard where he remained until 1961 when he transferred to the Naval Supply Research and Development Facility Bayonne New Jersey. Initially he was in charge of an Engineering Support Test Group and the drafting services for the whole Facility. Later he became a Project Engineer in the Food Services Facilities Branch with duties that included planning and designing new afloat and ashore messing facilities for the Navy. In 1966 he transferred to NAVSEC as a Project Engineer in the Design Work Study Section and in this capacity worked on selected projects and manning problems for new construction and also developed a computer program (Manpower Determination Model) that makes accurate crew predictions for feasibility studies. In 1969 he became Head of the Section. He has been active in the U.S. Army Reserve since his release from active duty and his duties have included command of an Engineer Company various Staff positions and his present assignment as Operations Officer for a Civil Affairs Group. He has completed the U. S. A rmy Corps of Engineers Career Course and the Civil Affairs Career Course and is presently enrolled in the U.S. Army Command and General Staff College non-resident course. Additionally he completed graduate studies at American University Washington D.C in 1972 receiving his MSTM degree in Technology of Management and is a member of ASE ASME CAA U. S. Naval Instit

The purpose of this paper is to discuss a system analysis technique called “Design Work Study”, that is used by the U.S. Navy for the development of improved ship control systems. The Design Work Study approach is one which brings about the most efficient and cost effective man‐machine combination for the ship control functions. Adherence to this process insures that the advantages of automation are balanced against incurred operational and maintenance expense. At present, U.S. Navy doctrine requires that certain ship operating stations, such as steering and propulsion control, be manned at specified ship conditions of readiness. Therefore, if personnel are needed to fulfill these combat environment obligations, excessive automation may only result in unnecessary additional acquisition costs and increased personnel skill requirements. The Design Work Study process can be applied to establish the required fine balance between the degree of built‐in automation and the shipboard manpower levels. In order to explain the techniques that are used for this process, the Authors will present a brief summary of the Design Work Study approach for optimizing shipboard control systems, including an explanation of the formal procedural tools that are applicable. In addition, a practical case study of ship control system design for one of the latest classes of Navy destroyers will be presented. This example will illustrate the resultant savings and benefits that can be realized by a judicious application of this technique. © 1976 American Society of Naval Engineers

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Unveiling long COVID symptomatology, co-occurrence trends, and symptom distress post SARS-CoV-2 infection

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Journal of infection and public health 2024年第7期17卷 102464页

作者： Shikha Kukreti Chun-Yin Yeh Yi-Jhen Chen Meng-Ting Lu Ming-Chi Li Yi-Yin Lai Chung-Yi Li Nai-Ying Ko Department of Nursing College of Medicine National Cheng Kung University Tainan Taiwan Department of Public Health College of Medicine National Cheng Kung University Taiwan. Department of Computer Science and Information Engineering National Cheng Kung University Taiwan. Department of Internal Medicine National Cheng Kung University Hospital College of Medicine National Cheng Kung University Tainan Taiwan. Centre of Infection Control College of Medicine National Cheng Kung University and Hospital Tainan Taiwan. Department of Public Health College of Medicine National Cheng Kung University Taiwan Department of Public Health College of Public Health China Medical University Taichung Department of Healthcare Administration College of Medical and Health Science Asia University Taichung Taiwan. International Doctoral Program in Nursing Department of Nursing College of Medicine National Cheng Kung University Tainan Taiwan. Electronic address: nyko@mail.ncku.edu.tw.

BACKGROUND:Long COVID, an emerging public health issue, is characterized by persistent symptoms following SARS-CoV-2 infection. This study aims to explore the relationship between post-COVID-19 symptomatology and patient distress employing Latent Class Analysis to uncover symptom co-occurrence patterns and their association with distress. METHODS:A cross-sectional study was conducted using an online survey among 240 participants from a university and affiliated hospital of southern Taiwan. The survey quantified distress due to persistent symptoms and assessed the prevalence of Long COVID, symptom co-occurrence, and latent symptom classes. Latent Class Analysis (LCA) identified distinct symptom patterns, and multiple regression models evaluated associations between symptom patterns, distress, and demographic factors. RESULTS:The study found that 80 % of participants experienced Long COVID, with symptoms persisting for over three months. Individuals with multiple COVID-19 infections showed a significant increase in general (β = 1.79), cardiovascular (β = 0.61), and neuropsychological symptoms (β = 2.18), and higher total distress scores (β = 6.35). Three distinct symptomatology classes were identified: "Diverse", "Mild", and "Severe" symptomatology. The "Mild Symptomatology" class was associated with lower distress (-10.61), while the "Severe Symptomatology" class showed a significantly higher distress due to symptoms (13.32). CONCLUSION:The study highlights the significant impact of Long COVID on individuals, with distinct patterns of symptomatology and associated distress. It emphasizes the cumulative effect of multiple COVID-19 infections on symptom severity and the importance of tailored care strategies.

关键词： Co-occurrence Distress Latent class Long COVID

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Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs

arXiv

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arXiv 2021年

作者： Sanders, Lauren M. Yang, Jason H. Scott, Ryan T. Qutub, Amina Ann Martin, Hector Garcia Berrios, Daniel C. Hastings, Jaden J.A. Rask, Jon Mackintosh, Graham Hoarfrost, Adrienne L. Chalk, Stuart Kalantari, John Khezeli, Kia Antonsen, Erik L. Babdor, Joel Barker, Richard Baranzini, Sergio E. Beheshti, Afshin Delgado-Aparicio, Guillermo M. Glicksberg, Benjamin S. Greene, Casey S. Haendel, Melissa Hamid, Arif A. Heller, Philip Jamieson, Daniel Jarvis, Katelyn J. Komarova, Svetlana V. Komorowski, Matthieu Kothiyal, Prachi Mahabal, Ashish Manor, Uri Mason, Christopher E. Matar, Mona Mias, George I. Miller, Jack Myers, Jerry G. Nelson, Charlotte Oribello, Jonathan Park, Seung-Min Parsons-Wingerter, Patricia Prabhu, R.K. Reynolds, Robert J. Saravia-Butler, Amanda Saria, Suchi Sawyer, Aenor Singh, Nitin Kumar Soboczenski, Frank Snyder, Michael Soman, Karthik Theriot, Corey A. van Valen, David Venkateswaran, Kasthuri Warren, Liz Worthey, Liz Zitnik, Marinka Costes, Sylvain V. Blue Marble Space Institute of Science Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Center for Emerging and Re-Emerging Pathogens Department of Microbiology Biochemistry and Molecular Genetics Rutgers New Jersey Medical School NewarkNJ07103 United States KBR Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States AI MATRIX Consortium Department of Biomedical Engineering University of Texas San Antonio and UT Health Sciences San AntonioTX78249 United States Biological Systems and Engineering Division Lawrence Berkeley National Lab. BerkeleyCA94608 United States DOE Agile BioFoundry EmeryvilleCA94608 United States Joint BioEnergy Institute EmeryvilleCA94608 United States Department of Physiology and Biophysics Weill Cornell Medicine New YorkNY10065 United States Office of the Center Director NASA Ames Research Center Moffett Field CA94035 United States Bay Area Environmental Research Institute NASA Ames Research Center Moffett Field CA94035 United States Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Department of Chemistry University of North Florida JacksonvilleFL32224 United States Center for Individualized Medicine Department of Surgery Department of Quantitative Health Sciences Mayo Clinic RochesterMN55905 United States Department of Emergency Medicine Center for Space Medicine Baylor College of Medicine HoustonTX77030 United States Department of Microbiology and Immunology Department of Otolaryngology Head and Neck Surgery University of California San Francisco San FranciscoCA94143 United States The Gilroy AstroBiology Research Group The University of Wisconsin - Madison MadisonWI53706 United States Weill Institute for Neurosciences Department of Neurology University of California San Francisco San FranciscoCA94158 United States Data Science Analytics Georgia Institute of Technology Lima15024

Space biology research aims to understand fundamental effects of spaceflight on organisms, develop foundational knowledge to support deep space exploration, and ultimately bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals, and humans for sustained multi-planetary life. To advance these aims, the field leverages experiments, platforms, data, and model organisms from both spaceborne and ground-analog studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally autonomous, light, agile, and intelligent to expedite knowledge discovery. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning, and modeling applications which offer key solutions toward these space biology challenges. In the next decade, the synthesis of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modeling and analytics, support maximally autonomous and reproducible experiments, and efficiently manage spaceborne data and metadata, all with the goal to enable life to thrive in deep space. © 2021, CC BY.

关键词： Predictive analytics

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Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health

arXiv

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arXiv 2021年

作者： Scott, Ryan T. Antonsen, Erik L. Sanders, Lauren M. Hastings, Jaden J.A. Park, Seung-Min Mackintosh, Graham Reynolds, Robert J. Hoarfrost, Adrienne L. Sawyer, Aenor Greene, Casey S. Glicksberg, Benjamin S. Theriot, Corey A. Berrios, Daniel C. Miller, Jack Babdor, Joel Barker, Richard Baranzini, Sergio E. Beheshti, Afshin Chalk, Stuart Delgado-Aparicio, Guillermo M. Haendel, Melissa Hamid, Arif A. Heller, Philip Jamieson, Daniel Jarvis, Katelyn J. Kalantari, John Khezeli, Kia Komarova, Svetlana V. Komorowski, Matthieu Kothiyal, Prachi Mahabal, Ashish Manor, Uri Martin, Hector Garcia Mason, Christopher E. Matar, Mona Mias, George I. Myers, Jerry G. Nelson, Charlotte Oribello, Jonathan Parsons-Wingerter, Patricia Prabhu, R.K. Qutub, Amina Ann Rask, Jon Saravia-Butler, Amanda Saria, Suchi Singh, Nitin Kumar Soboczenski, Frank Snyder, Michael Soman, Karthik van Valen, David Venkateswaran, Kasthuri Warren, Liz Worthey, Liz Yang, Jason H. Zitnik, Marinka Costes, Sylvain V. KBR Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States Department of Emergency Medicine Center for Space Medicine Baylor College of Medicine HoustonTX77030 United States Blue Marble Space Institute of Science Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States Department of Physiology and Biophysics Weill Cornell Medicine New YorkNY10065 United States Department of Urology Department of Radiology Stanford University School of Medicine StanfordCA94305 United States Bay Area Environmental Research Institute NASA Ames Research Center Moffett FieldCA94035 United States Mortality Research & Consulting Inc. HoustonTX77058 United States Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States UC Space Health Department of Orthopaedic Surgery University of California San Francisco San FranciscoCA94143 United States Center for Health AI Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine Anschutz Medical Campus AuroraCO80045 United States Hasso Plattner Institute for Digital Health at Mount Sinai Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New YorkNY10065 United States Department of Preventive Medicine and Community Health UTMB GalvestonTX77551 United States Human Health and Performance Directorate NASA Johnson Space Center HoustonTX77058 United States Department of Microbiology and Immunology Department of Otolaryngology Head and Neck Surgery University of California San Francisco San FranciscoCA94143 United States The Gilroy AstroBiology Research Group The University of Wisconsin Madison MadisonWI53706 United States Weill Institute for Neurosciences Department of Neurology University of California San Francisco San FranciscoCA94158 United States Department of Chemistry University of North Florida JacksonvilleFL32224 United States Data Scienc

Human space exploration beyond low Earth orbit will involve missions of significant distance and duration. To effectively mitigate myriad space health hazards, paradigm shifts in data and space health systems are necessary to enable Earth-independence, rather than Earth-reliance. Promising developments in the fields of artificial intelligence and machine learning for biology and health can address these needs. We propose an appropriately autonomous and intelligent Precision Space Health system that will monitor, aggregate, and assess biomedical statuses;analyze and predict personalized adverse health outcomes;adapt and respond to newly accumulated data;and provide preventive, actionable, and timely insights to individual deep space crew members and iterative decision support to their crew medical officer. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration, on future applications of artificial intelligence in space biology and health. In the next decade, biomonitoring technology, biomarker science, spacecraft hardware, intelligent software, and streamlined data management must mature and be woven together into a Precision Space Health system to enable humanity to thrive in deep space. © 2021, CC BY.

关键词： Earth (planet)

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Prototype of Learning Applications for Modern Cryptographic Techniques Using RC4 Algorithms to Support computer Security Courses

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Journal of Physics: Conference Series 2019年第1期1363卷

作者： Muhammad Iqbal Nasrul Nazar Cut Ita Erliana Defi Irwansyah Nuning Kurniasih Edi Susilo Akbar Iskandar Rini Suryani Supriyono Sudarmaji Erwin Putera Permana Alfian Erwinsyah Sujinah Haimah I Ketut Sudarsana Department of Computer System Universitas Pembangunan Panca Budi Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Departement of Agrotechnology University of Ratu Samban Bengkulu Indonesia Department of Informatics Universitas Malikussaleh Lhokseumawe Indonesia Departement of Agrotechnology Sekolah Tinggi Ilmu Pertanian Rejang Lebong Bengkulu Indonesia Department of Geography Education Universitas Prof. Dr. Hazairin SH. Bengkulu Bengkulu Indonesia Faculty of Computer Sciences Universitas Muhammadiyah Metro Indonesia Department of Elementary School Teacher Education Universitas Nusantara PGRI Kediri Indonesia Faculty of Education and Teacher Training IAIN Sultan Amai Gorontalo Indonesia Faculty of Education University Muhammadiyah of Surabaya Surabaya Indonesia Department of Education Management Universitas Prof. Dr. Hazairin SH.Bengkulu Bengkulu Indonesia Department of Religious Education Institut Hindu Dharma Negeri Denpasar Indonesia

The security of information in this global era is increasingly becoming a vital need in various aspects of life. An information will have a higher value when it comes to aspects of business decisions. This study presents a learning application to explain how to secure data using cryptographic techniques. This study aims to design a prototype learning application of cryptographic techniques using algorithm RC4 method. Based on the results of data analysis and after completing the design of RC4 algorithm cryptographic learning software, the authors found this software shows every step and stages of the processes (data input process (Plaintext or Ciphertext string), Key padding process (U), formation process in S-Box table, the Key-Flow formation process (K-keystream), encryption process and decryption process) contained in RC4 algorithm cryptography, so it can help understanding or learning work procedures of algorithms in the cryptographic method. Microsoft Visual Basic 2008 is an IDE (Integrated Development Environment) application that is used to create and develop software. In this application there were various features that facilitate programming such as compilation, debugging, project settings, designing and editing visual interfaces, and so on.

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The generation challenge programme platform: Semantic standards and workbench for crop science

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International Journal of Plant Genomics 2008年第1期2008卷 369601页

作者： Bruskiewich, Richard Senger, Martin Davenport, Guy Ruiz, Manuel Rouard, Mathieu Hazekamp, Tom Takeya, Masaru Doi, Koji Satoh, Kouji Costa, Marcos Simon, Reinhard Balaji, Jayashree Akintunde, Akinnola Mauleon, Ramil Wanchana, Samart Shah, Trushar Anacleto, Mylah Portugal, Arllet Ulat, Victor Jun Thongjuea, Supat Braak, Kyle Ritter, Sebastian Dereeper, Alexis Skofic, Milko Rojas, Edwin Martins, Natalia Pappas, Georgios Alamban, Ryan Almodiel, Roque Barboza, Lord Hendrix Detras, Jeffrey Manansala, Kevin Mendoza, Michael Jonathan Morales, Jeffrey Peralta, Barry Valerio, Rowena Zhang, Yi Gregorio, Sergio Hermocilla, Joseph Echavez, Michael Yap, Jan Michael Farmer, Andrew Schiltz, Gary Lee, Jennifer Casstevens, Terry Jaiswal, Pankaj Meintjes, Ayton Wilkinson, Mark Good, Benjamin Wagner, James Morris, Jane Marshall, David Collins, Anthony Kikuchi, Shoshi Metz, Thomas McLaren, Graham Van Hintum, Theo Crop Research Informatics Laboratory International Rice Research Institute (IRRI) DAPO Box 7777 Metro Manila Philippines Crop Research Informatics Laboratory International Maize and Wheat Improvement Center (CIMMYT) DF 06600 Mexico Apdo. Postal 6-641 Mexico Centre International de Recherche Agronomique Pour le Développement (CIRAD) 34398 Montpellier Cedex 5 Avenue Agropolis France Bioversity International 00057 Maccarese (Fiumicino) Rome Via dei Tre Denari 472/a Italy National Institute for Agrobiological Sciences (NIAS) Tsukuba Ibaraki 305-8602 Kannondai 2-1-2 Japan Empresa Brasileira de Pesquisa Agropecuaria (EMBRAPA) Brasilia DF 70770-900 Parque Estaçao Biologia Final W5 Norte Brazil Centro Internacional de la Papa (CIP) Lima 12 Avenida La Molina 1895 La Molina Peru International Crops Research Institute for the Semi-Arid Tropics Patancheru Andhra Pradesh 502324 India International Center for Agricultural Research in the Dry Areas Aleppo P.O. Box 5466 Syrian Arab Republic National Center for Genetic Engineering and Biotechnology 113 Thailand Science Park Klong Luang Pathumthani 12120 Phahonyothin Road Klong 1 Thailand Institute of Computer Science College of Arts and Sciences University of the Philippines Los Banos Laguna 4031 Philippines Department of Computer Science University of the Philippines Melchor Hall Diliman Quezon City 1101 Philippines National Center for Genome Resources Santa Fe NM 87505 2935 Rodeo Park Drive East United States Scottish Crop Research Institute Invergowrie Dundee DD2 5DA United Kingdom Department of Plant Breeding Cornell University Ithaca NY 14853 United States African Centre for Gene Technologies Lynnwood Ridge 0040 P.O. Box 75011 South Africa Department of Medical Genetics Faculty of Medicine University of British Columbia Vancouver BC V6T 1Z3 Canada School of Computing Science Simon Fraser Universtiy Burnaby BC V5A 1S6 8888 University Drive Canada Bioinformatics Graduate Program Genome Sciences Centre BC

The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform;(ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data;(iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making.

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AIRR community curation and standardised representation for immunoglobulin and T cell receptor germline sets

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Immunoinformatics (Amsterdam, Netherlands) 2023年 10卷 100025页

作者： William D Lees Scott Christley Ayelet Peres Justin T Kos Brian Corrie Duncan Ralph Felix Breden Lindsay G Cowell Gur Yaari Martin Corcoran Gunilla B Karlsson Hedestam Mats Ohlin Andrew M Collins Corey T Watson Christian E Busse Institute of Structural and Molecular Biology Birkbeck College London England. Human-Centered Computing and Information Science Institute for Systems and Computer Engineering Technology and Science Porto Portugal. Peter O'Donnell Jr. School of Public Health UT Southwestern Medical Center Dallas TX USA. Bioengineering Program Faculty of Engineering Bar-Ilan University Ramat Gan Israel. Department of Biochemistry and Molecular Genetics School of Medicine University of Louisville KY USA. Department of Biological Sciences Simon Fraser University Burnaby BC Canada. Fred Hutchinson Cancer Research Center Seattle WA USA. Peter O'Donnell Jr. School of Public Health Department of Immunology School of Biomedical Sciences UT Southwestern Medical Center Dallas TX USA. Department of Microbiology Tumor and Cell Biology Karolinska Institutet Stockholm Swede. Department of Immunotechnology and SciLifeLab Lund University Lund Sweden. School of Biotechnology and Biomolecular Sciences University of New South Wales Sydney NSW Australia. Division of B Cell Immunology German Cancer Research Center Heidelberg Germany.

Analysis of an individual's immunoglobulin or T cell receptor gene repertoire can provide important insights into immune function. High-quality analysis of adaptive immune receptor repertoire sequencing data depends upon accurate and relatively complete germline sets, but current sets are known to be incomplete. Established processes for the review and systematic naming of receptor germline genes and alleles require specific evidence and data types, but the discovery landscape is rapidly changing. To exploit the potential of emerging data, and to provide the field with improved state-of-the-art germline sets, an intermediate approach is needed that will allow the rapid publication of consolidated sets derived from these emerging sources. These sets must use a consistent naming scheme and allow refinement and consolidation into genes as new information emerges. Name changes should be minimised, but, where changes occur, the naming history of a sequence must be traceable. Here we outline the current issues and opportunities for the curation of germline IG/TR genes and present a forward-looking data model for building out more robust germline sets that can dovetail with current established processes. We describe interoperability standards for germline sets, and an approach to transparency based on principles of findability, accessibility, interoperability, and reusability.

关键词： AIRR-seq Immune receptor Immune receptor germline Immune receptor repertoire Rep-seq

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Erratum to: Diet Versus Phylogeny: a Comparison of Gut Microbiota in Captive Colobine Monkey Species

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Microbial ecology 2018年第2期75卷 528页

作者： Vanessa L Hale Chia L Tan Kefeng Niu Yeqin Yang Rob Knight Qikun Zhang Duoying Cui Katherine R Amato Microbiome Program Mayo Clinic 200 First St. SW Rochester MN 55905 USA. vreynolds@***. LVDI International San Marcos CA 92078 USA. Fanjingshan National Nature Reserve Administration Tongren China. Department of Life Sciences and Systems Biology University of Turin 10123 Turin Italy. Department of Pediatrics University of California San Diego La Jolla CA 92093 USA. Department of Computer Science and Engineering University of California San Diego La Jolla CA 92093 USA. Zhejiang Institute of Microbiology Hangzhou Zhejiang China. Beijing Key Laboratory of Captive Wildlife Technologies Beijing Zoo Beijing 100044 China. Department of Anthropology Northwestern University Evanston IL 60208 USA.

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