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Author Correction: A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis

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Nature communications 2019年第1期10卷 2956页

作者： Lohith Madireddy Kicheol Kim Xiaoming Jia Adam Santaniello Stacy J. Caillier Bruce A. C. Cree Roland Henry Stephen L. Hauser Jorge R. Oksenberg Sergio E. Baranzini Nikolaos A. Patsopoulos Philip De Jager Chris Cotsapas Matthew R. Lincoln David A. Hafler Steffan D. Bos Hanne F. Harbo Tone Berge Elisabeth G. Celius Ashley Beecham Jacob McCauley Margaret A. Pericak-Vance Till F. M. Andlauer Christiane Gasperi Bernhard Hemmer Lisa F. Barcellos Luisa Bernardinelli Filippo Martinelli-Boneschi David R. Booth Graeme J. Stewart Farren Briggs Jonathan Haines Manuel Comabella Giancarlo Comi Federica Esposito Sandra D’Alfonso Katrina Dedham Pierre Duquette Efthimios Dardiotis Bertrand Fontaine An Goris Bénédicte Dubois Pierre-Antoine Gourraud Georgios Hadjigeorgiou Clive Hawkins Seema Kalra Rogier Hintzen Dana Horakova Noriko Isobe Jun-ichi Kira Michael Khalil Ingrid Kockum Tomas Olsson Christina M. Lill Felix Luessi Frauke Zipp Roland Martin Annette Oturai Aarno Palotie Janna Saarela Adrian Ivinson Bruce V. Taylor Alastair Compston Stephen Sawcer Weill Institute for Neurosciences Department of Neurology University of California San Francisco San Francisco CA 94158 USA Bakar Institute for Computational Health Science. University of California San Francisco San Francisco CA 94158 USA Systems Biology and Computer Science Program Ann Romney Center for Neurological Diseases Department of Neurology and Division of Genetics Department of Medicine Brigham & Women’s Hospital Harvard Medical School Boston MA 02115 USA Broad Institute of Harvard University and Massachusetts Institute of Technology Cambridge MA 02142 USA Department of Neurology Center for Translational and Computational Neuroimmunology and Multiple Sclerosis Center Columbia University Medical Center New York NY 10032 USA Departments of Neurology Yale School of Medicine 300 George St New Haven CT 06511 USA Department of Genetics Yale School of Medicine 300 George St New Haven CT 06511 USA Institute of Clinical Medicine University of Oslo Oslo 0318 Norway Department of Neurology Oslo University Hospital Oslo 0424 Norway Department of Mechanical Electronics and Chemical Engineering Oslo Metropolitan University Oslo 0167 Norway Institute of Health and Society University of Oslo Oslo 0318 Norway John P. Hussman Institute for Human Genomics University of Miami Miller School of Medicine Miami FL 33136 USA Dr. John T. Macdonald Foundation Department of Human Genetics University of Miami Miller School of Medicine Miami FL 33136 USA Department of Neurology Klinikum rechts der Isar School of Medicine Technical University of Munich 81675 Munich Germany Munich Cluster for Systems Neurology (SyNergy) 81377 Munich Germany Division of Epidemiology School of Public HealthUniversity of California 324 Stanley Hall MC#3220 Berkeley CA 94720 USA Section of Biostatistics Neurophyisiology and Psychiatry Unit of medical and genomic statistics Universita of Pavia Pavia 27100 Italy Department of Biomedical Sciences for Health Univers

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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Nat Genet:单细胞分析解开结直肠癌细胞的神秘面纱

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现代生物医学进展 2017年第15期17卷 I0003-I0003页

作者： Huipeng Li, Elise T Courtois, Debarka Sengupta, Yuliana Tan Shyam Prabhakar Elise T Courtois, Yuliana Tan Paul Robson Debarka Sengupta Kok Hao Chen, Jolene Jie Lin Goh Paul Jongjoon Choi Say Li Kong, Axel M Hillmer Iain Beehuat Tan Clarinda Chua Iain Beehuat Tan Lim Kiat Hon Wah Siew Tan Mark Wong Lawrence J K Wee Iain Beehuat Tan Paul Robson Paul Robson Paul Robson Computational and Systems Biology Genome Institute of Singapore Singapore Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Department of Computer Science and Engineering and Center for Computational Biology Indraprastha Institute of Information Technology Delhi India Synthetic Biology Genome Institute of Singapore Singapore Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Department of Medical Oncology National Cancer Centre Singapore Singapore Department of Pathology Singapore General Hospital Singapore Department of Colorectal Surgery Singapore General Hospital Singapore Data Analytics Department Institute for Infocomm Research Singapore Program in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore The Jackson Laboratory for Genomic Medicine Farmington Connecticut USA Department of Genetics and Genome Sciences Institute for Systems Genomics University of Connecticut Farmington Connecticut USA Department of Biological Sciences National University of Singapore Singapore.

结合单细胞基因组学和计算机技术，一个研究团队（包括来自杰克逊实验室（JAx）单细胞生物学主任Paul Robson博士在内）鉴定出了11种结直肠癌肿瘤的癌细胞组成及邻近的非癌细胞。这对于更好的肿瘤靶向诊断和治疗很重要。”使用单细胞测... 详细信息

结合单细胞基因组学和计算机技术，一个研究团队（包括来自杰克逊实验室（JAx）单细胞生物学主任Paul Robson博士在内）鉴定出了11种结直肠癌肿瘤的癌细胞组成及邻近的非癌细胞。这对于更好的肿瘤靶向诊断和治疗很重要。”使用单细胞测序。”JAX科学家、这篇发表在Nature Genetics上的文章共同第一作者Elise Courtois说道。”我们可以根据肿瘤中的细胞组成将结直肠癌进一步分类。因为每种亚型的肿瘤病人生存率存在差别，我们的方法将为肿瘤医生提供更多的关于肿瘤预后和治疗的信息。”

关键词：单细胞分析结直肠癌癌细胞 Nat 细胞组成肿瘤病计算机技术细胞生物学

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Maintaining constant towing tension between cable ship and burying system under sea waves by hybrid FUZZY P + ID controller

Maintaining constant towing tension between cable ship and b...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Qi Chen Wei Li Xiaohui Wang Yan Li Shuo Li Bin Xian Robotics State Key Laboratory Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing P. R. China Department of Computer & Electrical Engineering and Computer Science California State University Bakersfield CA USA School of Electrical Engineering and Automation Tianjin University Tianjin China

In this paper, we propose a hybrid FUZZY P + ID controller to stabilize the towing cable tension between a cable ship and a burying system. First, we develop the model of a winch system driven by valve-controlled hydraulic motors and evaluate the step responses yielded by the conventional PID and the proposed FUZZY P+ID controllers using simulations. The comparative studies show that the control performance yielded by the FUZZY P+ID controller is superior. We replace the existing PID controller implemented on the towing winch with the FUZZY P + ID controller for burying cable tasks at speed up to 1 knot under sea waves with significant variations (peak-to-peak) from 1.5 to 2.5 meters. The real applications demonstrate that the FUZZY P + ID controller is much more robust than the conventional PID controller.

关键词： Winches Valves Automation Mathematical model Marine vehicles Torque

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Linearization approach for modeling power electronics devices in power systems

Linearization approach for modeling power electronics device...

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作者： Liang, Xiaodong Electrical Engineering Program School of Engineering and Computer Science Washington State University VancouverWA98686 United States

Power electronics devices are extensively used in renewable energy resources, modern power grids, and industrial facilities. In this paper, a linearization approach is proposed as a generic dynamic modeling method for power electronics devices in power systems. The associated control system is included in the modeling. This approach can be readily used for renewable energy resources, such as wind turbines and solar photovoltaic systems, and for power electronics devices in power systems, such as variable frequency drives (VFDs). The developed dynamic models are suitable for power systems dynamic studies. To demonstrate the effectiveness of the proposed approach, the dynamic load model of a system, consisting of a voltage source inverter type low-voltage six-pulse VFD and an induction motor, is developed in this paper, and a sample motor drive system is provided as a case study to verify the accuracy of the developed dynamic load model. © 2013 IEEE.

关键词： Linearization

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Work in progress: Using videotelephony to provide independent technical critique of student capstone projects

Work in progress: Using videotelephony to provide independen...

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121st ASEE Annual Conference and Exposition: 360 Degrees of engineering Education

作者： Schilling, Walter W. Estell, John K. Al-Olimat, Khalid S. Software Engineering program Milwaukee School of Engineering Milwaukee WI United States Department of Computer Engineering and Computer Science Ohio Northern University United States

As part of the requirement for ABET accreditation, an engineering program is expected to have a curriculum culminating in a major design experience, commonly referred to as either a "senior design" or a "capstone" project, based on the knowledge and skills acquired in earlier course work. One challenge that programs face is providing appropriate technical and professional feedback to students on their capstone projects. For example, students may be working in an application domain in which the faculty member has limited knowledge, or may be using newer technologies that the faculty member has not used before. To overcome these problems, it is often advantageous for the team to partner with an industrial mentor. The industrial mentor can provide technical assistance to the project as well as provide impartial and unbiased feedback on the status of the project. However, this is not always feasible, as not all campuses are located in urban areas, and project stakeholders may not be local to the institution. This work in progress article describes the first part of a two part project to overcome some of these problems. In this portion of the project, capstone teams work directly with an alumnus who serves as "External Industrial Reviewer" on the project using remote video conferencing. As the students complete significant milestones, deliverables are critiqued by External Industrial Reviewer who is impartial to the project. Students receive feedback on the deliverable, which can then be incorporated into future projects. This article describes the concept as well as provides a preliminary assessment of the technique. © American Society for engineering Education, 2013.

关键词： Students

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PAPR reduction in an OFDM system using recursive clipping and filtering technique

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WSEAS Transactions on Communications 2014年第1期13卷 291-297页

作者： Islam, Anamul Ahmed, N. Ahamed, Nizam Uddin Rahman, Matiur Aljunid, S.A. Dept. of Applied Physics and Electronic Engineering University of Rajshahi Bangladesh School of Computer and Communication Engineering University Malaysia Perlis Malaysia Biomedical Engineering Program Mechatronic Engineering University Malaysia Perlis Malaysia College of Computer Science and Information System Najran University Saudi Arabia

An Orthogonal Frequency Division Multiplexing (OFDM) scheme is expected as an efficient technique for next generation wireless communications. However, high Peak to Average Power Ration (PAPR) of OFDM system is the main drawback which degrades the transmitter power efficiency causes poor performance of the system. To reduce PAPR of OFDM signal, several works on clipping technique have been proposed. This paper is incorporated the improvement of the PAPR and Bit Error Rate (BER) performance using clipping method. It has been shown from the result that by employing the recursive clipping and filtering, 11.45 dB of PAPR of original OFDM signal is reduced down to 4.77 dB. Hence, BER is also increased significantly. This research is carried out through MATLAB simulation and gradually measured the effect of PAPR on BER under AWGN channel for 16QAM scheme with 256 points OFDM. Moreover, it is studied the effect of OFDM signal while passing through High Power Amplifier (HPA). Finally, the PAPR reduction technique such as recursive clipping and filtering (RCF) is implemented.

关键词： Orthogonal frequency division multiplexing

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FERA 2015 - second Facial Expression Recognition and Analysis challenge

FERA 2015 - second Facial Expression Recognition and Analysi...

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International Conference on Automatic Face and Gesture Recognition

作者： Michel F. Valstar Timur Almaev Jeffrey M. Girard Gary McKeown Marc Mehu Lijun Yin Maja Pantic Jeffrey F. Cohn School of Computer Science University of Nottingham UK Department of Psychology University of Pittsburgh Pittsburgh USA School of Psychology Queen's University Belfast Belfast UK Department of Psychology Webster University Private Vienna Vienna AT Department of Computer Science Binghamton University Binghamton USA Department of Computing Imperial College London London UK Electrical Engineering University of Twente The Netherlands Robotics Institute Carnegie Mellon University Pittsburgh USA

Despite efforts towards evaluation standards in facial expression analysis (e.g. FERA 2011), there is a need for up-to-date standardised evaluation procedures, focusing in particular on current challenges in the field. One of the challenges that is actively being addressed is the automatic estimation of expression intensities. To continue to provide a standardisation platform and to help the field progress beyond its current limitations, the FG 2015 Facial Expression Recognition and Analysis challenge (FERA 2015) will challenge participants to estimate FACS Action Unit (AU) intensity as well as AU occurrence on a common benchmark dataset with reliable manual annotations. Evaluation will be done using a clear and well-defined protocol. In this paper we present the second such challenge in automatic recognition of facial expressions, to be held in conjunction with the 11 IEEE conference on Face and Gesture Recognition, May 2015, in Ljubljana, Slovenia. Three sub-challenges are defined: the detection of AU occurrence, the estimation of AU intensity for pre-segmented data, and fully automatic AU intensity estimation. In this work we outline the evaluation protocol, the data used, and the results of a baseline method for the three sub-challenges.

关键词： Gold Reliability Estimation Databases Feature extraction Face recognition Training

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A New Integrated Fuzzifier Evaluation and Selection(NIFEs) Algorithm for Fuzzy Clustering

A New Integrated Fuzzifier Evaluation and Selection(NIFEs) A...

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2015 Workshop 7

作者： Chanpaul Jin Wang Hua Fang Sun Kim Ann Moormann Honggang Wang Division of Biostatistics and Health Services Research Department of Quantitative Health Science UMass Medical School Department of Electrical & Computer Engineering University of Massachusetts Dartmouth Department of Nursing College of Nursing and Health Sciences University of Massachusetts Program of Molecular Medicine UMass Medical School

Fuzzy C-means(FCM) is simple and widely used for complex data pattern recognition and image analyses. However, selecting an appropriate fuzzifier(m) is crucial in identifying an optimal number of patterns and achieving higher clustering accuracy, which few studies have investigated. Built upon two existing methods on selecting fuzzifier, we developed an integrated fuzzifier evaluation and selection algorithm and tested it using real datasets. Our findings indicate that the consistent optimal number of clusters can be learnt from testing different fuzzifiers for each dataset and the fuzzifier with the lowest value for this consistency should be selected for clustering. Our evaluation also shows that the fuzzifier impacts the clustering accuracy. For longitudinal data with missing values, m = 2 could be an empirical rule to start fuzzy clustering, and the best clustering accuracy was achieved for tested data, especially using our multiple-imputation based fuzzy clustering.

关键词： Fuzzifier Fuzzy C-Means Multiple Imputation-Based Fuzzy Clustering(MIFuzzy) Missing Data Longitudinal Data

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Towards experimental analysis of challenge scenarios in robotics 12

Towards experimental analysis of challenge scenarios in robo...

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12th International Symposium on Experimental robotics, ISER 2010

作者： Hollinger, Geoffrey A. Singh, Sanjiv Computer Science Department Viterbi School of Engineering University of Southern California Los AngelesCA90089 United States Robotics Institute School of Computer Science Carnegie Mellon University PittsburghPA15213 United States

ISBN: (纸本)9783642285714

We explore the idea of simulated experimental analysis for challenge scenarios in robotics using the search and secure problem from the Multi Autonomous Ground-robotic International Challenge (MAGIC). The MAGIC problem requires a team of heterogeneous robots to locate, classify, and secure a number of targets in an urban environment with indoor and outdoor areas. We introduce a framework for solving the coordination aspects of the challenge by providing guaranteed clearing strategies (i.e., strategies that ensure coming into contact with any adversarial target). The proposed method allows for repair of the clearing schedule after robot failure, as well as a fall-back strategy if clearing is no longer possible. We analyze scenarios taken directly from the competition, and we utilize repeated simulated trials to validate the hypothesis that strategies designed for locating worst-case targets tend to be more robust to failure than strategies designed for locating average-case targets. Thus, more conservative worst-case methods would tend to perform better if the competition were run many times. However, riskier average-case strategies may win in a single competition. These results demonstrate how insight can be gained from repeated simulated analysis of challenge scenarios in robotics. © Springer-Verlag Berlin Heidelberg 2014.

关键词： robotics

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Creation and analysis of biochemical constraint-based models: The COBRA Toolbox v3.0

arXiv

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arXiv 2017年

作者： Heirendt, Laurent Arreckx, Sylvain Pfau, Thomas Mendoza, Sebastián N. Richelle, Anne Heinken, Almut Haraldsdóttir, Hulda S. Wachowiak, Jacek Keating, Sarah M. Vlasov, Vanja Magnusdóttir, Stefania Ng, Chiam Yu Preciat, German Žagare, Alise Chan, Siu H.J. Aurich, Maike K. Clancy, Catherine M. Modamio, Jennifer Sauls, John T. Noronha, Alberto Bordbar, Aarash Cousins, Benjamin El Assal, Diana C. Valcarcel, Luis V. Apaolaza, Iñigo Ghaderi, Susan Ahookhosh, Masoud Guebila, Marouen Ben Kostromins, Andrejs Sompairac, Nicolas Le, Hoai M. Ma, Ding Sun, Yuekai Wang, Lin Yurkovich, James T. Oliveira, Miguel A.P. Vuong, Phan T. El Assal, Lemmer P. Kuperstein, Inna Zinovyev, Andrei Scott Hinton, H. Bryant, William A. Aragón Artacho, Francisco J. Planes, Francisco J. Stalidzans, Egils Maass, Alejandro Vempala, Santosh Hucka, Michael Saunders, Michael A. Maranas, Costas D. Lewis, Nathan E. Sauter, Thomas Palsson, Bernhard Ø. Thiele, Ines Fleming, Ronan M.T. Luxembourg Centre for Systems Biomedicine University of Luxembourg 6 avenue du Swing BelvauxL-4367 Luxembourg Life Sciences Research Unit University of Luxembourg 6 avenue du Swing BelvauxL-4367 Luxembourg University of Chile Blanco Encalada 2085 Santiago Chile Department of Pediatrics University of California San Diego School of Medicine San DiegoCA92093 United States Hinxton CambridgeCB10 1SD United Kingdom Department of Chemical Engineering Pennsylvania State University University University ParkPA16802 United States Department of Physics University of California San Diego 9500 Gilman Dr. San DiegoCA92093 United States Bioinformatics and Systems Biology Program University of California San Diego San DiegoCA United States Sinopia Biosciences San DiegoCA United States School of Computer Science Algorithms and Randomness Center Georgia Institute of Technology AtlantaGA United States Biomedical Engineering and Sciences Department TECNUN University of Navarra Paseo de Manuel Lardizabal 13 San Sebastian20018 Spain Institute of Microbiology and Biotechnology University of Latvia Jelgavas iela 1 RigaLV-1004 Latvia Department of Management Science and Engineering Stanford University StanfordCA94305-4026 United States Bioengineering Department University of California San Diego San DiegoCA United States Utah State University Research Foundation 1695 North Research Park Way North LoganUT84341 United States Centre for Integrative Systems Biology and Bioinformatics Department of Life Sciences Imperial College London London United Kingdom Department of Mathematics University of Alicante Spain California Institute of Technology Computing and Mathematical Sciences MC 305-16 1200 E. California Blvd. PasadenaCA91125 United States Mathomics Center for Mathematical Modeling University of Chile Beauchef 851 Santiago Chile Novo Nordisk Foundation Center for Biosustainability University of California San Diego San DiegoCA92093 Uni

COnstraint-Based Reconstruction and Analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive software suite of interoperable COBRA methods. It has found widespread applications in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. Version 3.0 includes new methods for quality controlled reconstruction, modelling, topological analysis, strain and experimental design, network visualisation as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimisation solvers for multi-scale, multi-cellular and reaction kinetic modelling, respectively. This protocol can be adapted for the generation and analysis of a constraint-based model in a wide variety of molecular systems biology scenarios. This protocol is an update to the COBRA Toolbox 1.0 and 2.0. The COBRA Toolbox 3.0 provides an unparalleled depth of constraint-based reconstruction and analysis methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Data integration

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