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Proceedings of the Digital Image Computing: Technqiues and applications (DICTA)

作者： Dongyan Guo Jian Zhang Min Xu Xiangjian He Minxian Li Chunxia Zhao School of Computer Science and Engineering Nanjing University of Science and Technology China Advanced Analytics Institute & School of Software University of Technology Sydney Australia Center for Innovation in IT Services and Applications (iNEXT) University of Technology Sydney Australia

ISBN: (纸本)9781479954100

Playing a vital role, saliency has been widely applied for various image analysis tasks, such as content-aware image retargeting, image retrieval and object detection. It is generally accepted that saliency detection can benefit from the integration of multiple visual features. However, most of the existing literatures fuse multiple features at saliency map level without considering cross-feature information, i.e. generate a saliency map based on several maps computed from an individual feature. In this paper, we propose a Multiple Feature Distance Preserving (MFDP) model to seamlessly integrate multiple visual features through an alternative optimization process. Our method outperforms the state-of-the-arts methods on saliency detection. Saliency detected by our method is further cooperated with seam carving algorithm and significantly improves the performance on image retargeting.

关键词： Feature extraction Visualization Mathematical model Image color analysis Equations Educational institutions Computational modeling

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Solving the Klein-Gordon equation using Fourier spectral methods: A benchmark test for computer performance 23

Solving the Klein-Gordon equation using Fourier spectral met...

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23rd High Performance Computing Symposium, HPC 2015, Part of the 2015 Spring Simulation Multi-Conference, SpringSim 2015

作者： Aseeri, S. Batrašev, O. Icardi, M. Leu, B. Liu, A. Li, N. Muite, B.K. Müller, E. Palen, B. Quell, M. Servat, H. Sheth, P. Speck, R. Van Moer, M. Vienne, J. KAUST Supcrcomputing Laboratory 4700 King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Arvutitcaduse Instituut Tartu Ülikool Liivi 2 Tartu50409 Estonia Stochastic Numerics Group 4700 King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Electrical and Computer Engineering University of Michigan Ann ArborMI48109-2122 United States Numerical Algorithms Group Wilkinson House Jordan Hill Road Oxford0X2 8DR United Kingdom Numerical Mathematics Group 4700 King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Mathematical Sciences University of Bath BathBA2 7 AY United Kingdom CAEN Advanced Computing University of Michigan Ann ArborMI48109-2094 United States Lnstitut für Analysis und Scientific Computing Technische Universität Wien Wiedner Haupstrasse 8-10 Wien1040 Austria Compulcr Sciences Department BSC UPC c/Jordi Girona Barcelona Calalunya08034 Spain Biomedical Engineering University of Michigan Ann ArborMI48109-2122 United States Jülich Supercomputing Centre Forschungszentrum Jülich GmbH Germany Germany National Center for Supercomputing Applications University of Illinois at Urbiina-Chanipaign UrbanaIL61801 United States Texas Advanced Computing Center University of Texas at Austin AustinTX78758-4497 United States

ISBN: (纸本)9781510810600

The cubic Klein-Gordon equation is a simple but non-trivial partial differential equation whose numerical solution has the main building blocks required for the solution of many other partial differential equations. In this study, the library 2DE-COMP&FFT is used in a Fourier spectral scheme to solve the Klein-Gordon equation and strong scaling of the code is examined on thirteen different machines for a problem size of 5123. The results are useful in assessing likely performance of other parallel fast Fourier transform based programs for solving partial differential equations. The problem is chosen to be large enough to solve on a workstation, yet also of interest to solve quickly on a supercomputer, in particular for parametric studies. Unlike the Linpack benchmark, a high ranking will not be obtained by simply building a bigger computer. © 2015 Aseeri et al.

关键词： Fast Fourier transforms

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Towards a Realistic Risk Assessment Methodology for Insider Threats of Information Misuse

Towards a Realistic Risk Assessment Methodology for Insider ...

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Frontiers of Information technology (FIT)

作者： Maaz Bin Ahmad Saeed-Ur-Rehman Adeel Akram Muhammad Asif Department of Electrical & Computer Engineering Center for Advanced Studies in Engineering (CASE) Islamabad Pakistan Department of Electrical & Computer Engineering Muhammad Ali Jinnah University (MAJU) Islamabad Pakistan Faculty of Software & Computer Engineering University of Engineering & Technology Taxila Pakistan

The problem of insider threats is not new to organizations and research community. Organization cannot afford any kinds of attacks on their confidential information and resources either from insiders or out-siders. The damage done by insiders is more severe than that of external attackers due to their knowledge about the system and potential targets. It has been observed by studying previous case studies of insider attacks that insiders usually get involve in some unusual or suspicious activities prior to launching actual attacks. So observing these kinds of activities and taking proper actions in time may help to avoid such kinds of attacks. In this paper a risk assessment methodology has been presented to compute the threat levels of insiders. Appropriate actions may be taken by knowing about the threat level of each user in order to avoid actual attacks. The methodology not only incorporates technical measures but also some psychological indicators to detect insiders. The difference of this methodology from the previous ones is that it provides a practical way of quantization of risks for insider threats. The methodology is simulated in a test network against different scenarios and results showed that it efficiently categorized users according to their threat level. So it provides a base to deploy non uniform security policies among the users thus reducing overall processing overheads.

关键词： Organizations Monitoring computers Security Psychology software Distance measurement

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A Platform for Real-time Acquisition and Analysis of Physiological Data in Hospital Emergency Departments

A Platform for Real-time Acquisition and Analysis of Physiol...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Jason B. Smith Andrew T. Reisner Shwetha Edla Jianbo Liu Stephanie Liddle Jaques Reifman Department of Defense Biotechnology High Performance Computing Software Applications Institute (BHSAI) Telemedicine and Advanced Technology Research Center (TATRC) BHSAI TATRC USAMRMC Department of Biomedical Engineering Massachusetts General Hospital

ISBN: (纸本)9781424479276

An opportunity exists for automated clinical decision support, in which raw source data from a conventional physiological monitoring system are continuously streamed to an independent analysis platform. Such a system would enable a wider range of functionality than offered by the source monitoring system. Although vendor solutions for this purpose are emerging, we developed our own system in order to control the expense and to permit forensic analysis of the internal core functionality of the system. In this report, we describe a platform that can provide decision support for trauma patients in an Emergency Department (ED). System evaluation spanned 39 days, and included a total of 2200 patient session hrs of real-time monitoring. We highlight the technical issues that we confronted, including protection of the core monitoring network, the real-time communication of electronic medical data, and the reliability of the real-time analysis. Detailing these nuanced technical issues may be valuable to other software developers or for those interested in investing in a vendor solution for similar functionality.

关键词： Monitoring Biomedical monitoring Real-time systems software Servers Testing Reliability

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Tournament selection based artificial bee colony algorithm with elitist strategy

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8916卷 387-396页

作者： Zhang, Meng-Dan Zhan, Zhi-Hui Li, Jing-Jing Zhang, Jun Department of Computer Science Sun Yat-sen University 510275 China Key Lab. Machine Intelligence and Advanced Computing Ministry of Education China Engineering Research Center of Supercomputing Engineering Software MOE China Key Lab. Software Technology Education Department of Guangdong Province China School of Computer Science South China Normal University China

Artificial bee colony (ABC) algorithm is a novel heuristic algorithm inspired from the intelligent behavior of honey bee swarm. ABC algorithm has a good performance on solving optimization problems of multivariable functions and has been applied in many fields. However, traditional ABC algorithm chooses solutions on the onlooker stage with roulette wheel selection (RWS) strategy which has several disadvantages. Firstly, RWS is suitable for maximization optimization problem. The fitness value has to be converted when solving minimization optimization problem. This makes RWS difficult to be generally used in real-world applications. Secondly, RWS has no any parameter that can control the selection pressure. Therefore, RWS is not easy to adapt to various optimization problems. This paper proposes a tournament selection based ABC (TSABC) algorithm to avoid these disadvantages of RWS based ABC. Moreover, this paper proposes an elitist strategy that can be applied to traditional ABC, TSABC, and any other ABC variants, so as to avoid the phenomenon that ABC algorithm may abandon the globally best solution in the scout stage. We compare the performance of traditional ABC and TSABC on a set of benchmark functions. The experiment results show that TSABC is more flexible and can be efficiently adapted to solve various optimization problems by controlling the selection pressure. © Springer International Publishing Switzerland 2014.

关键词： Optimization

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Generating software test data by particle swarm optimization

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8886卷 37-47页

作者： Jia, Ya-Hui Chen, Wei-Neng Zhang, Jun Li, Jing-Jing School of Information Science and Technology Sun Yat-sen University Guangzhou China School of Advanced Computing Sun Yat-sen University Guangzhou China Key Lab. Machine Intelligence and Advanced Computing Ministry of Education China Engineering Research Center of Supercomputing Engineering Software MOE China School of Computer Science South China Normal University Guangzhou China

Search-based method using meta-heuristic algorithms is a hot topic in automatic test data generation. In this paper, we develop an automatic test data generating tool named particle swarm optimization data generation tool (PSODGT). The PSODGT is characterized by the following two features. First, the PSODGT adopts the condition-decision coverage (C/DC) as the criterion of software testing, aiming to build an efficient test data set that covers all conditions. Second, the PSODGT uses a particle swarm optimization (PSO) approach to generate test data set. In addition, a new position initialization technique is developed for PSO. Instead of initializing the test data randomly, the proposed technique uses the previously-found test data that can reach the target condition as the initial positions so that the search speed of PSODGT can be further accelerated. The PSODGT is tested on four practical programs. Experimental results show that the proposed PSO approach is promising. © Springer International Publishing Switzerland 2014.

关键词： software testing

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Load balance aware genetic algorithm for task scheduling in cloud computing

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8886卷 644-655页

作者： Zhan, Zhi-Hui Zhang, Ge-Yi Ying-Lin Gong, Yue-Jiao Zhang, Jun Department of Computer Science Sun Yat-sen University Guangzhou510006 China Key Lab. Machine Intelligence and Advanced Computing Ministry of Education China Engineering Research Center of Supercomputing Engineering Software MOE China Key Lab. Software Technology Education Department Guangdong Province China School of Sofware Engineering Sun Yat-sen University Guangzhou510006 China Department of Psychology Sun Yat-sen university 510275 China

This paper proposes to solve the task scheduling problem in cloud computing by using a load balance aware genetic algorithm (LAGA) with Minmin and Max-min methods. Task scheduling problems are of great importance in cloud computing, and become especially challenging when taking load balance into account. Our proposed LAGA algorithm has several advantages when solving this kind of problems. Firstly, by introducing the time load balance (TLB) model to help establish the fitness function with makespan, the algorithm benefits from the ability to find the solution that performs best on load balance among a set of solutions with the same makespan. More importantly, the interaction between makespan and TLB helps the algorithm to minimize makespan in the same time. Secondly, Min-min and Max-min methods are used to produce promising individuals at the beginning of evolution, leading to noticeable improvement of evolution efficiency. We evaluated LAGA on several task scheduling problems and compared with a Min-min, Max-min improved version of genetic algorithm (MMGA), which does not use the TLB strategy. The results show that LAGA can obtain very competitive results with good load balancing properties, and outperform MMGA in both makespan and TLB objectives. © Springer International Publishing Switzerland 2014.

关键词： Genetic algorithms

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XXIV World Allergy Congress 2015 Seoul, Korea. 14-17 October 2015 Abstracts

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WORLD ALLERGY ORGANIZATION JOURNAL 2016年第1期9卷 1-206页

作者： [Anonymous] Korea University College of Medicine Guro Hospital Seoul South Korea College of Medicine Korea University Seoul South Korea Korea University Guro Hospital Seoul South Korea Seoul National University Boramae Hospital Seoul South Korea Division of Clinical Immunology Faculty of Medicine University of Debrecen Debrecen Hungary Meiji Pharmaceutical University Tokyo Japan Suri Medical Foundation Hospital Uttar Pradesh State India Shahid Beheshti University Tehran Iran Airlangga University Teaching Hospital Surabaya Indonesia Tokyo Metropolitan Police Hospital Tokyo Japan Shinichiro KogaSamsung Changwon Hospital Seoul South Korea Sapporo Tokushukai Hospital Sapporo Japan Department of Dermatology Yonsei University College of Medicine Seoul South Korea Brain Korea 21 PLUS Project for Medical Science Yonsei University College of Medicine Seoul South Korea Sureyyapasa Chest Diseases and Chest Surgery Training Hospital Istanbul Turkey Kangnam Sacred Heart Hospital Seoul South Korea Sakai City Medical Center Sakai Japan Osaka University Suita Japan Yonsei University College of Medicine Seoul South Korea Osaka-Minami Medical Center Kawachinagano Japan Inha University College of Medicine Incheon South Korea Inha University Hospital Incheon South Korea Center for Rhinology and Allergology Wiesbaden Wiesbaden Germany Leti Pharma Gmbh Witten Germany Postgraduate Institute of Medical Education and Research Chandigarh India West Bengal Technical University Kolkata India Institute of Microbiology Academy of Sciences of the Czech Republic Prague Czech Republic Seoul National University Hospital Seoul South Korea Ent and Allergy Centre(INDIA) Panchkula India University of Santo Tomas Hospital Manila Philippines University of Santo Tomas Faculty of Medicine Manila Philippines Kyung Hee University Hospital at Gang-Dong Seoul South Korea Sangji University Wonju South Korea Division of Allergy and Immunology Department of Internal Medicine Yonsei University Colle

A1 Pirfenidone inhibits TGF-b1-induced extracellular matrix production in nasal polyp-derived fibroblasts Jae-Min Shin, Heung-Man Lee, Il-Ho Park A2 The efficacy of a 2-week course of oral steroid in the treatment of chronic spontaneous urticaria refractory to antihistamines Hyun-Sun Yoon, Gyeong Yul Park A3 The altered distribution of follicular t helper cells may predict a more pronounced clinical course of primary sjögren’s syndrome Margit Zeher A4 Betamethasone suppresses Th2 cell development induced by langerhans cell like dendritic cells Katsuhiko Matsui, Saki Tamai, Reiko Ikeda A5 An evaluation of variousallergens in cases of allergic bronchial asthma at lucknow and neighbouring districts by intradermal skintest Drsushil Suri, Dranu Suri A6 Evaluation ferqency of ADHD in childhood asthma Marzieh Heidarzadeh Arani A7 Steven johnson syndrome caused by typhoid fever in a child Azwin Lubis, Anang Endaryanto A8 Chronic Bronchitis with Radio Contrast Media Hypersensitivity: A Case with Hypothesized GINA Step 1 Asthma Shinichiro Koga A9 The association between asthma and depression in Korean adult : An analysis of the fifth korea national health and nutrition examination survey (2010-2012) Lee Ju Suk A10 Management of allergic disease exacerbations in pregnancy Yasunobu Tsuzuki A11 Subcutaneous immunotherapy mouse model for atopic dermatitis Seo Hyeong Kim, Jung U Shin, Ji Yeon Noh, Shan Jin, Shan Jin, Hemin Lee, Jungsoo Lee, Chang Ook Park, Kwang Hoon Lee, Kwang Hoon Lee A12 Atopic disease and/or atopy are risk factors for local anesthetic allergy in patients with history of hypersensitivity reactions to drugs? Fatma Merve Tepetam A13 Food hypersensitivity in patients with atopic dermatitis in Korea Chun Wook Park, Jee Hee Son, Soo Ick Cho, Yong Se Cho, Yun Sun Byun, Yoon Seok Yang, Bo Young Chung, Hye One Kim, Hee Jin Cho A14 Anaphylaxis caused by an ant (Brachyponera chinensis) in Japan Yoshinori Katada, Toshio Tanaka, Akihiko Nakabayashi, Koji Nishida, Kenichi A

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RETRACTED: Improvement mechanism of resistance random access memory with supercritical CO 2 fluid treatment

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The Journal of Supercritical Fluids 2014年 85卷 183-189页

作者： Kuan-Chang Chang Jung-Hui Chen Tsung-Ming Tsai Ting-Chang Chang Syuan-Yong Huang Rui Zhang Kai-Huang Chen Yong-En Syu Geng-Wei Chang Tian-Jian Chu Guan-Ru Liu Yu-Ting Su Min-Chen Chen Jhih-Hong Pan Kuo-Hsiao Liao Ya-Hsiang Tai Tai-Fa Young Simon M. Sze Jen-Wei Huang Department of Materials and Optoelectronic Science National Sun Yat-Sen University 70 Lien-hai Road Kaohsiung 804 Taiwan Department of Chemistry National Kaohsiung Normal University Kaohsiung Taiwan Department of Physics National Sun Yat-Sen University 70 Lien-hai Road Kaohsiung 804 Taiwan Advanced Optoelectronics Technology Center National Cheng Kung University Taiwan School of Software and Microelectronics Peking University Beijing 100871 People's Republic of China Department of Electronics Engineering and Computer Science Tung-Fang Design Institute Kaohsiung Taiwan Department of Photonics and the Institute of Electro-Optical Engineering National Chiao Tung University Hsinchu 300 Taiwan Department of Mechanical and Electro-Mechanical Engineering Kaohsiung 804 Taiwan Department of Electronics Engineering and Institute of Electronics National Chiao Tung University Hsinchu 300 Taiwan Department of Physics ROC Military Academy Kaohsiung 83055 Taiwan

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

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

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

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

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

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