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Gene expression imputation across multiple brain regions provides insights into schizophrenia risk (vol 51, pg 659, 2019)

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NATURE GENETICS 2019年第6期51卷 1068-1068页

作者： Huckins, Laura M. Dobbyn, Amanda Ruderfer, Douglas M. Hoffman, Gabriel Wang, Weiqing Pardinas, Antonio F. Rajagopal, Veera M. Als, Thomas D. Nguyen, Hoang T. Girdhar, Kiran Boocock, James Roussos, Panos Fromer, Menachem Kramer, Robin Domenici, Enrico Gamazon, Eric R. Purcell, Shaun Demontis, Ditte Borglum, Anders D. Walters, James T. R. O'Donovan, Michael C. Sullivan, Patrick Owen, Michael J. Devlin, Bernie Sieberts, Solveig K. Cox, Nancy J. Im, Hae Kyung Sklar, Pamela Stahl, Eli A. Pamela Sklar Division of Psychiatric Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics and Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Psychiatry Icahn School of Medicine at Mount Sinai New York NY USA Icahn Institute for Genomics and Multiscale Biology Icahn School of Medicine at Mount Sinai New York NY USA Vanderbilt University Medical Center Nashville TN USA MRC Centre for Neuropsychiatric Genetics and Genomics Cardiff University Cardiff UK Department of Biomedicine Aarhus University Aarhus Denmark The Lundbeck Foundation Initiative for Integrative Psychiatric Research iPSYCH Denmark Center for Integrative Sequencing Aarhus University Aarhus Denmark Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA Human Brain Collection Core National Institute of Mental Health Bethesda MD USA Laboratory of Neurogenomic Biomarkers Centre for Integrative Biology (CIBIO) University of Trento Trento Italy Clare Hall University of Cambridge Cambridge UK University of North Carolina at Chapel Hill Chapel Hill NC USA Karolinska Institutet Stockholm Sweden Department of Psychiatry University of Pittsburgh Pittsburgh PA USA Systems Biology Sage Bionetworks Seattle WA USA Section of Genetic Medicine Department of Medicine University of Chicago Chicago IL USA Integrated Technology Research Laboratories Pharmaceutical Research Division Takeda Pharmaceutical Company Limited Fujisawa Japan Neuropsychiatry Section Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Neuropsychiatric Signaling Program Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Psychiatry JJ Peters Virginia Medical Center Bronx NY USA Department of Neuroscience Icahn School of Medicine at Mount Sinai New York New York NY USA Friedman Brain Institute

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

关键词： Gene expression Genome-wide association studies Schizophrenia Transcriptomics

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A node placement optimization method for watershed underwater sensor networks 9

A node placement optimization method for watershed underwate...

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9th ACM International Conference on Underwater Networks and systems, WUWNet 2014

作者： Barbosa, Gentil V. Letouze, Patrick Xavier, Adilson E. Department of Computer Science UFT - Universidade Federal do Tocantins PESC Brazil Department of Computer Science UFT - Universidade Federal do Tocantins MCS - Postgraduate Program of System's Computational Modeling Brazil PESC - Postgraduate Program of System's Engineering and Computation UFRJ - Universidade Federal do Rio de Janeiro Brazil

ISBN: (纸本)9781450332774

Given a set of underwater sensors coordinates that are usually determined by a specialist for the design of a watershed monitoring system, where should be placed the sinks and the base station? The answer may be the minimization of the Variable Internode Distance. In such cases, a two dimensional architecture is acceptable because it is a shallow water system. Hence, in this paper, it is proposed a two-level node distance minimization for Underwater Wireless Sensor Network for monitoring systems. The mathematical method employed for optimization is the Hyperbolic Smoothing approach and the proposed method includes the placement of the base-station in the algorithm. Copyright 2014 ACM.

关键词： Base stations

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Real-Time Music Tracking Based on a Weightless Neural Network

Real-Time Music Tracking Based on a Weightless Neural Networ...

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International Conference on Complex, Intelligent and Software Intensive systems, CISIS

作者： Diego F. P. De Souza Felipe M.G. Franca Priscila M.V. Lima Syst. Eng. & Comput. Sci. Program - COPPE Universidade Federal do Rio de Janeiro Rio de Janeiro RJ BR System Engineering and Computer Science Program - COPPE Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil Inst. Tercio Pacitti (NCE) Univ. Fed. do Rio de Janeiro Janeiro Brazil

Music tracking is a useful technique for many music related tasks. Some applications include evaluating musicians performance, automatic score page turning and syncing music lyrics. In this work, we describe a WiSARD-based system for real-time music tracking and evaluate the performance of the corresponding implementation. Given any audio example, the system is capable of recognizing which point of the original signal is currently playing and of dynamically tracking it. In other words, if the music restarts or jumps to another position, the system is capable of following it. This is accomplished thanks to the low complexity training and classifying of the models used, which continually keep track of all possible points of the music, and not only of the current neighboring region. Experiments are provided in order to analyze the performance of the system in three test scenarios: tracking continuous playing, tracking multiple jumps and self predicting errors. The final results demonstrate that the system is efficient even when applied to musics with some level of repetitions and short periods of silence.

关键词： Training Random access memory Music Robot sensing systems Hidden Markov models Neurons

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Identification of K most vulnerable nodes in multi-layered network using a new model of interdependency

Identification of K most vulnerable nodes in multi-layered n...

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IEEE Conference on computer Communications Workshops, INFOCOM Wksps

作者： Arunabha Sen Anisha Mazumder Joydeep Banerjee Arun Das Randy Compton Computer Science and Engineering Program School of Computing Informatics and Decision System Engineering Arizona State University Tempe Arizona

The critical infrastructures of a nation including the power grid and the communication network are highly interdependent. Recognizing the need for a deeper understanding of the interdependency in a multi-layered network, significant efforts have been made by the research community in the last few years to achieve this goal. Accordingly a number of models have been proposed and analyzed. Unfortunately, most of the models are over simplified and, as such, they fail to capture the complex interdependency that exists between entities of the power grid and the communication networks involving a combination of conjunctive and disjunctive relations. To overcome the limitations of existing models, we propose a new model that is able to capture such complex interdependency relations. Utilizing this model, we provide techniques to identify the K most “vulnerable” nodes of an interdependent network. We show that the problem can be solved in polynomial time in some special cases, whereas for some others, the problem is NP-complete. We establish that this problem is equivalent to computation of a fixed point of a multilayered network system and we provide a technique for its computation utilizing Integer Linear programming. Finally, we evaluate the efficacy of our technique using real data collected from the power grid and the communication network that span the Maricopa County of Arizona.

关键词： Equations Communication networks Mathematical model Power grids Power system faults Power system protection Nonhomogeneous media

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On the impact of coding parameters on storage requirement of region-based fault tolerant distributed file system design

On the impact of coding parameters on storage requirement of...

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International Conference on Computing, Networking and Communications (ICNC)

作者： Sujogya Banerjee Arun Das Anisha Mazumder Zahra Derakhshandeh Arunabha Sen Computer Science and Engineering Program School of Computing Informatics and Decision System Engineering Arizona State University Tempe Arizona

Advances in technology have resulted in Internet-scale deployment of storage systems such as peer-to-peer storage and cloud storage, where data is distributed over multiple storage nodes in a networked environment. In these environments the storage nodes are often commodity machines and are susceptible to failure. The notion of fault domain, introduced by Microsoft Azure, captures the fault-tolerance aspects of a data center. A fault domain is defined as a set of servers all of which become inaccessible when a single fault (such as the failure of a switch or a router) occurs in the data center. As such a fault domain can be viewed as a spatially correlated or region based failure. In order to enhance reliability through redundancy, maximum distance separable (MDS) codes such as Reed-Solomon codes and (N, K) codings are utilized. In this paper we present analytical results demonstrating that the choice of the coding parameters N and K may have significant impact on storage that will be necessary to achieve reliability. We present a polynomial time algorithm for optimal storage allocation in a mesh network and we conduct extensive experimentation to evaluate the impact of the coding parameters N and K on the storage requirement to provide all region fault tolerance with varying size of the mesh and the fault region.

关键词： Color Image color analysis Encoding Silicon Peer-to-peer computing Fault tolerant systems Fault tolerance

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Root Cause Analysis of Failures in Interdependent Power-Communication Networks

Root Cause Analysis of Failures in Interdependent Power-Comm...

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MILCOM, Military Communications Conference

作者： Arun Das Joydeep Banerjee Arunabha Sen Computer Science and Engineering Program School of Computing Informatics and Decision System Engineering Arizona State University Tempe Arizona

ISBN: (纸本)9781479967711

Studies on communication network robustness, though extensive, have primarily focused on standalone networks. However, real world communication networks do not operate in isolation, but instead are part of complex interdependent ecosystems that function together as a comprehensive symbiotic unit. For instance, communication networks of today are highly dependent on the power infrastructure and hence, any efforts to improve the robustness of communication networks must necessarily take into account the vulnerabilities of the power infrastructure and their shared interdependencies. For example, event-induced failures (failures caused by natural disasters or terrorist attacks), on any of these two infrastructures can trigger further failures (triggered failures) into the system through a cascading process due to the interdependencies between the networks. In such an interdependent system where an event induced failure can cascade and result in a much larger combined (event-induced plus triggered) failure, it may be imperative to identify the original event-induced failure for the purpose of post fault diagnostics, or for pre-cascade network strengthening. This ascertainment of event-induced original failure, or the Root Cause of Failure, from combined failures in interdependent Power-Communication networks is the main focus of this paper. We model interdependencies between the two infrastructures using the recently proposed Implicative Interdependency Model. We introduce the Root Cause of Failure problem, and prove it to be NP-Complete. We also provide optimal solutions using ILP, and provide an O(ln(n)) approximation algorithm. Finally, we validate our analytical results through experiments in the power communication network of Maricopa County, Arizona.

关键词： Communication networks Silicon Approximation algorithms Computational modeling Power system faults Power system protection Approximation methods

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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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Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

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Scientific data 2017年第1期4卷 170179页

作者： Jason Flannick Christian Fuchsberger Anubha Mahajan Tanya M Teslovich Vineeta Agarwala Kyle J Gaulton Lizz Caulkins Ryan Koesterer Clement Ma Loukas Moutsianas Davis J McCarthy Manuel A Rivas John R B Perry Xueling Sim Thomas W Blackwell Neil R Robertson N William Rayner Pablo Cingolani Adam E Locke Juan Fernandez Tajes Heather M Highland Josee Dupuis Peter S Chines Cecilia M Lindgren Christopher Hartl Anne U Jackson Han Chen Jeroen R Huyghe Martijn van de Bunt Richard D Pearson Ashish Kumar Martina Müller-Nurasyid Niels Grarup Heather M Stringham Eric R Gamazon Jaehoon Lee Yuhui Chen Robert A Scott Jennifer E Below Peng Chen Jinyan Huang Min Jin Go Michael L Stitzel Dorota Pasko Stephen C J Parker Tibor V Varga Todd Green Nicola L Beer Aaron G Day-Williams Teresa Ferreira Tasha Fingerlin Momoko Horikoshi Cheng Hu Iksoo Huh Mohammad Kamran Ikram Bong-Jo Kim Yongkang Kim Young Jin Kim Min-Seok Kwon Juyoung Lee Selyeong Lee Keng-Han Lin Taylor J Maxwell Yoshihiko Nagai Xu Wang Ryan P Welch Joon Yoon Weihua Zhang Nir Barzilai Benjamin F Voight Bok-Ghee Han Christopher P Jenkinson Teemu Kuulasmaa Johanna Kuusisto Alisa Manning Maggie C Y Ng Nicholette D Palmer Beverley Balkau Alena Stančáková Hanna E Abboud Heiner Boeing Vilmantas Giedraitis Dorairaj Prabhakaran Omri Gottesman James Scott Jason Carey Phoenix Kwan George Grant Joshua D Smith Benjamin M Neale Shaun Purcell Adam S Butterworth Joanna M M Howson Heung Man Lee Yingchang Lu Soo-Heon Kwak Wei Zhao John Danesh Vincent K L Lam Kyong Soo Park Danish Saleheen Wing Yee So Claudia H T Tam Uzma Afzal David Aguilar Rector Arya Tin Aung Edmund Chan Carmen Navarro Ching-Yu Cheng Domenico Palli Adolfo Correa Joanne E Curran Dennis Rybin Vidya S Farook Sharon P Fowler Barry I Freedman Michael Griswold Daniel Esten Hale Pamela J Hicks Chiea-Chuen Khor Satish Kumar Benjamin Lehne Dorothée Thuillier Wei Yen Lim Jianjun Liu Marie Loh Solomon K Musani Sobha Puppala William R Scott Loïc Yengo Sian-Tsung Tan Herman A Taylor Farook Thameem Gregory Wilson Tien Yin Wong Pål Rasmu Department of Molecular Biology Massachusetts General Hospital Boston Massachusetts USA. Program in Medical and Population Genetics Broad Institute Cambridge Massachusetts USA. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor Michigan USA. Wellcome Trust Centre for Human Genetics Nuffield Department of Medicine University of Oxford Oxford UK. Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology Cambridge Massachusetts USA. Department of Statistics University of Oxford Oxford UK. Genetics of Complex Traits University of Exeter Medical School University of Exeter Exeter UK. MRC Epidemiology Unit Institute of Metabolic Science University of Cambridge Cambridge UK. Department of Twin Research and Genetic Epidemiology King's College London London UK. Oxford Centre for Diabetes Endocrinology and Metabolism Radcliffe Department of Medicine University of Oxford Oxford UK. Department of Human Genetics Wellcome Trust Sanger Institute Hinxton Cambridgeshire UK. School of Computer Science McGill University Montreal Quebec Canada. McGill University and Génome Québec Innovation Centre Montreal Quebec Canada. Human Genetics Center The University of Texas Graduate School of Biomedical Sciences at Houston The University of Texas Health Science Center at Houston Houston Texas USA. Department of Biostatistics Boston University School of Public Health Boston Massachusetts USA. National Heart Lung and Blood Institute's Framingham Heart Study Framingham Massachusetts USA. Medical Genomics and Metabolic Genetics Branch National Human Genome Research Institute National Institutes of Health Bethesda Maryland USA. Department of Biostatistics Harvard School of Public Health Boston Massachusetts USA. Chronic Disease Epidemiology Swiss Tropical and Public Health Institute University of Basel Basel Switzerland. Institute of Genetic Epidemiology Helmholtz Zentrum München German R

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

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An improved parameterized approach for real time optimal motion planning of AUV moving in dynamic environment

An improved parameterized approach for real time optimal mot...

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IEEE Conference on Robotics, Automation and Mechatronics

作者： Wenhao Luo Jun Peng Jing Wang Department of Automation Key Laboratory of System Control And Information Processing Shanghai China School of Information Science and Engineering Hunan Engineering Laboratory Changsha China Computer Engineering Program Bethune-Cookman University Daytona Beach FL USA

In this paper, we present an improved analytic method to the optimal trajectory generation of an autonomous underwater vehicle (AUV) in a dynamic environment. The proposed approach explicitly incorporates both the AUV kinematic and the geometric constraints due to dynamic obstacles and the terrain while rendering the near-shortest path by a performance index related to the path length. In particular, the proposed design is based on a family of parameterized trajectories determined by three adjustable parameters, which provides a unified way to reformulate the geometric constraints and performance index into a set of parameterized constraint equations. To that end, such a constrained optimization problem boils down to optimize those adjustable parameters, which can be analytically solved in the parameter space. The proposed solution enhances the methodologies of real-time path planning for robots in 3D environment. Simulation results verify the effectiveness of the proposed method.

关键词： Trajectory Planning Vehicle dynamics Dynamics Collision avoidance Kinematics Optimization

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A unified optimization method for real-time trajectory generation of mobile robots with kinodynamic constraints in dynamic environment

A unified optimization method for real-time trajectory gener...

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IEEE Conference on Robotics, Automation and Mechatronics

作者： Wenhao Luo Jun Peng Weirong Liu Jing Wang Wentao Yu Department of Automation Key Laboratory of System Control And Information Processing Shanghai China School of Information Science and Engineering Hunan Engineering Laboratory for Advanced Controland Intelligent Automation Changsha China Computer Engineering Program Bethune-Cookman University Daytona Beach FL USA

This paper presents an efficient analytic method for a mobile robot to determine a collision-free trajectory with unified optimization. The robot kinodynamic constraints and the geometric constraints due to obstacles are addressed by considering a set of constrained inequalities from parameterized trajectories model. Two optimal performance matrices are employed to assess optimization problems. Particularly, both the constraints and performance functions are incorporated by similar forms in terms of trajectory parameters, which thereby can be considered in a uniform way. A parameter space of adjustable trajectory parameters is constructed to solve the unified optimization problem with constraints and results in more flexible and better optimal performance. The proposed approach is complete and enhances methods of deterministic real-time planning by overcoming typical drawbacks as intermediate configuration, curvature discontinuities, vertical singularities and incomplete optimization. Simulation results verify the validity and superiority of the proposed method.

关键词： Trajectory Robot kinematics Collision avoidance Mobile robots Acceleration Optimization

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