scholarly journals HeartBioPortal2.0: new developments and updates for genetic ancestry and cardiometabolic quantitative traits in diverse human populations

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Bohdan B Khomtchouk ◽  
Christopher S Nelson ◽  
Kasra A Vand ◽  
Salvator Palmisano ◽  
Robert L Grossman
Keyword(s):  
Data Storage ◽  
Web Application ◽  
Quantitative Traits ◽  
Large Scale ◽  
Genome Wide Association Study ◽  
User Authentication ◽  
Ethnically Diverse ◽  
Human Populations ◽  
Diverse Populations ◽  
Computing Platform

Abstract Cardiovascular disease (CVD) is the leading cause of death worldwide for all genders and across most racial and ethnic groups. However, different races and ethnicities exhibit different rates of CVD and its related cardiorenal and metabolic comorbidities, suggesting differences in genetic predisposition and risk of onset, as well as socioeconomic and lifestyle factors (diet, exercise, etc.) that act upon an individual’s unique underlying genetic background. Here, we present HeartBioPortal2.0, a major update to HeartBioPortal, the world’s largest CVD genetics data precision medicine platform for harmonized CVD-relevant genetic variants, which now enables search and analysis of human genetic information related to heart disease across ethnically diverse populations and cardiovascular/renal/metabolic quantitative traits pertinent to CVD pathophysiology. HeartBioPortal2.0 is structured as a cloud-based computing platform and knowledge portal that consolidates a multitude of CVD-relevant genomic data modalities into a single powerful query and browsing interface between data and user via a user-friendly web application publicly available to the scientific research community. Since its initial release, HeartBioPortal2.0 has added new cardiovascular/renal/metabolic disease–relevant gene expression data as well as genetic association data from numerous large-scale genome-wide association study consortiums such as CARDIoGRAMplusC4D, TOPMed, FinnGen, AFGen, MESA, MEGASTROKE, UK Biobank, CHARGE, Biobank Japan and MyCode, among other studies. In addition, HeartBioPortal2.0 now includes support for quantitative traits and ethnically diverse populations, allowing users to investigate the shared genetic architecture of any gene or its variants across the continuous cardiometabolic spectrum from health (e.g. blood pressure traits) to disease (e.g. hypertension), facilitating the understanding of CVD trait genetics that inform health-to-disease transitions and endophenotypes. Custom visualizations in the new and improved user interface, including performance enhancements and new security features such as user authentication, collectively re-imagine HeartBioPortal’s user experience and provide a data commons that co-locates data, storage and computing infrastructure in the context of studying the genetic basis behind the leading cause of global mortality. Database URL: https://www.heartbioportal.com/

scholarly journals HeartBioPortal2.0: new developments and updates for genetic ancestry and cardiometabolic quantitative traits in diverse human populations

2020 ◽  
Author(s):  
Bohdan B. Khomtchouk ◽  
Kasra A. Vand ◽  
Christopher S. Nelson ◽  
Salvator Palmisano ◽  
Robert L. Grossman
Keyword(s):  
Cardiovascular Disease ◽  
Data Storage ◽  
Web Application ◽  
Quantitative Traits ◽  
Large Scale ◽  
Genome Wide Association Study ◽  
Ethnically Diverse ◽  
Next Generation Sequencing Data ◽  
Human Populations ◽  
Diverse Populations

AbstractCardiovascular disease (CVD) is the leading cause of death worldwide for both genders and across most racial and ethnic groups. However, different races and ethnicities exhibit different rates of cardiovascular disease and its related cardiorenal and metabolic co-morbidities, suggesting differences in genetic predisposition and risk of onset, as well as socioeconomic and lifestyle factors (diet, exercise, etc.) that act upon an individual’s unique underlying genetic background. Here we present HeartBioPortal2.0, a major update to HeartBioPortal, the world’s largest CVD genetics data precision medicine platform for harmonized CVD-relevant genetic variants, which now enables search and analysis of human genetic information related to heart disease across ethnically diverse populations and cardiovascular/renal/metabolic quantitative traits pertinent to CVD pathophysiology. HeartBioPortal2.0 is structured as a cloud-based computing platform and knowledge portal that consolidates a multitude of CVD-relevant next-generation sequencing data modalities into a single powerful query and browsing interface between data and user via a user-friendly web application publicly available to the scientific research community. Since its initial release, HeartBioPortal2.0 has added new cardiovascular/renal/metabolic disease relevant gene expression data as well as genetic association data from numerous large-scale genome-wide association study (GWAS) consortiums such as CARDIoGRAMplusC4D, TOPMed, FinnGen, AFGen, MESA, MEGASTROKE, UK Biobank, CHARGE, Biobank Japan, MyCode, among other studies. In addition, HeartBioPortal2.0 now includes support for quantitative traits and ethnically diverse populations, allowing users to investigate the shared genetic architecture of any gene or its variants across the continuous cardiometabolic spectrum from health (e.g., blood pressure traits) to disease (hypertension), facilitating the understanding of CVD trait genetics that inform health-to-disease transitions and endophenotypes. Custom visualizations in the new and improved user interface (UI), including performance enhancements and new security features such as user authentication collectively re-imagine HeartBioPortal’s user experience and provide a data commons that co-locates data, storage and computing infrastructure in the context of studying the genetic basis behind the leading cause of global mortality.Database URLhttps://www.heartbioportal.com/

scholarly journals Microservice Security Agent Based On API Gateway in Edge Computing

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4905 ◽  
Author(s):  
Rongxu Xu ◽  
Wenquan Jin ◽  
Dohyeun Kim
Keyword(s):  
Data Storage ◽  
User Authentication ◽  
Edge Computing ◽  
Security And Privacy ◽  
Agent Based ◽  
Computing Platform ◽  
Authentication Mechanism ◽  
Computing Paradigm ◽  
Security Agent ◽  
Secure Authentication

Internet of Things (IoT) devices are embedded with software, electronics, and sensors, and feature connectivity with constrained resources. They require the edge computing paradigm, with modular characteristics relying on microservices, to provide an extensible and lightweight computing framework at the edge of the network. Edge computing can relieve the burden of centralized cloud computing by performing certain operations, such as data storage and task computation, at the edge of the network. Despite the benefits of edge computing, it can lead to many challenges in terms of security and privacy issues. Thus, services that protect privacy and secure data are essential functions in edge computing. For example, the end user’s ownership and privacy information and control are separated, which can easily lead to data leakage, unauthorized data manipulation, and other data security concerns. Thus, the confidentiality and integrity of the data cannot be guaranteed and, so, more secure authentication and access mechanisms are required to ensure that the microservices are exposed only to authorized users. In this paper, we propose a microservice security agent to integrate the edge computing platform with the API gateway technology for presenting a secure authentication mechanism. The aim of this platform is to afford edge computing clients a practical application which provides user authentication and allows JSON Web Token (JWT)-based secure access to the services of edge computing. To integrate the edge computing platform with the API gateway, we implement a microservice security agent based on the open-source Kong in the EdgeX Foundry framework. Also to provide an easy-to-use approach with Kong, we implement REST APIs for generating new consumers, registering services, configuring access controls. Finally, the usability of the proposed approach is demonstrated by evaluating the round trip time (RTT). The results demonstrate the efficiency of the system and its suitability for real-world applications.

scholarly journals SISTEM INFORMASI PROGRAM MAHASISWA WIRAUSAHA UNIVERSITAS NEGERI PADANG

2019 ◽  
Vol 7 (2) ◽  
pp. 138
Author(s):  
Wahidin Saputra ◽  
Elfi Tasrif
Keyword(s):  
Higher Education ◽  
Information System ◽  
Data Storage ◽  
Web Application ◽  
High Performance ◽  
Large Scale ◽  
Ministry Of Education ◽  
Application Development ◽  
Directorate General ◽  
Student Program

Entrepreneurship plays an important role in Indonesia's development. Entrepreneurship is important because of the magnitude of the role played by entrepreneurs in overcoming various problems of national economic development such as poverty alleviation, high unemployment, the Entrepreneurial Student Program is a program of the Ministry of Education and Culture's Directorate General of Higher Education implemented and developed by universities. Padang State University is one of the universities that has received assistance from the Directorate General of Higher Education. The Entrepreneurial Student Program Information System built has a web-based display, where with this information system students or other users can access anytime and anywhere to get information about the Entrepreneurial Student Program. For proposers, they can input their proposals directly through this information system and facilitate data storage for managers of the Entrepreneurial Student Program. This system is built using the Yii2 Framework, a component-based PHP programming that has high performance for large-scale web application development. Keywords: Information Systems, Entrepreneurial Student Programs, Yii2 Framework

scholarly journals GWAS identifies nine nephrolithiasis susceptibility loci related with metabolic metabolic and crystallization pathways

2019 ◽  
Author(s):  
Chizu Tanikawa ◽  
Yoichiro Kamatani ◽  
Chikashi Terao ◽  
Masayuki Usami ◽  
Atsushi Takahashi ◽  
...  
Keyword(s):  
Genetic Background ◽  
Quantitative Traits ◽  
Large Scale ◽  
Genetic Factors ◽  
Genome Wide Association Study ◽  
Genetic Variations ◽  
Susceptibility Loci ◽  
Genome Wide ◽  
Host Genetic ◽  
Host Genetic Factors

ABSTRACTNephrolithiasis is a common urological trait disorder with acute pain. Although previous studies have identified various genetic variations associated with nephrolithiasis, the host genetic factors remain largely unidentified. To identify novel nephrolithiasis loci in the Japanese population, we performed large-scale GWAS (Genome wide association study) using 11,130 cases and 187,639 controls, followed by a replication analysis using 2,289 cases and 3,817 controls. The analysis identified 14 significant loci, including 9 novel loci on 2p23.2-3, 6p21.2, 6p12.3, 6q23.2, 16p12.3, 16q12.2, 17q23.2, 19p13.12, and 20q13.2. Interestingly, 10 of the 14 regions showed a significant association with any of 16 quantitative traits, including metabolic, kidney-related, and electrolyte traits, suggesting a common genetic background among nephrolithiasis patients and these quantitative traits. Four novel loci are related to the metabolic pathway, while the remaining 10 loci are associated with the crystallization pathway. Our findings demonstrate the crucial roles of genetic variations in the development of nephrolithiasis.SIGNIFICANCE STATEMENTNephrolithiasis is a common urothelial disorders with frequent recurrence rate, but its genetic background is largely remained unidentified. Previous GWAS identified 6 genetic factors in total. Here we performed a GWAS using more than 200,000 samples in the Japanese populations, and identified 14 significant loci and nine of them are novel. We also found that 10 of the 14 loci showed a significant association with any of 16 quantitative traits, including metabolic, kidney-related, and electrolyte traits (BMI, eGFR, UA, Ca etc). All 14 significant loci are associate with either metabolic or crystallization pathways. Thus, our findings elucidated the underlying molecular pathogenesis of nephrolithiasis.

scholarly journals Enhanced Framework for Ensuring Privacy Preserving Image Retrieval in Cloud

2019 ◽  
Vol 8 (12) ◽  
pp. 2127-2132
Keyword(s):  
Data Storage ◽  
Large Scale ◽  
Research Work ◽  
Image Data ◽  
Cloud Service ◽  
Sensitive Information ◽  
Cloud Platform ◽  
Privacy And Security ◽  
Computing Platform ◽  
Computing Platforms

Large scale of images data sets are being produced every day by various digital devices. Due to huge computational jobs make people seizure to cloud platforms for their efficient & economical reckoning resources. These computing platforms in which assets are provided as services of the internet. Sensitive information stored in cloud makes more challenging in data security and access control. Once data is uploaded to cloud-platform, the privacy and security of image-data fully depend and believe upon cloud service provider honesty. Our proposed work deals with securing image where high protections are applied on multimedia contents. This paper deals with studies security challenges algorithms lies in image at the time of constructing cloud platform. In this a new enhanced security technique investigated, includes secure by using computation and encryption, act as a security information guard for high secrecy in cloud platform data storage areas. In our research work, cipher-text image is created and performing encryption-decryption at User level. Data hiding and ECC (Elliptic curve cryptosystem) based watermarking technique at cloud computing platform.

scholarly journals Estimating indirect parental genetic effects on offspring phenotypes using virtual parental genotypes derived from sibling and half sibling pairs

2020 ◽  
Author(s):  
Liang-Dar Hwang ◽  
Justin D Tubbs ◽  
Justin Luong ◽  
Mischa Lundberg ◽  
Gunn-Helen Moen ◽  
...  
Keyword(s):  
Web Application ◽  
Large Scale ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Genome Wide Association Study ◽  
Late Onset ◽  
Genetic Effects ◽  
Association Analyses ◽  
Sibling Pairs ◽  
Genome Wide

AbstractIndirect parental genetic effects may be defined as the influence of parental genotypes on offspring phenotypes over and above that which results from the transmission of genes from parents to children. However, given the relative paucity of large-scale family-based cohorts around the world, it is difficult to demonstrate parental genetic effects on human traits, particularly at individual loci. In this manuscript, we illustrate how parental genetic effects on offspring phenotypes, including late onset diseases, can be estimated at individual loci in principle using large-scale genome-wide association study (GWAS) data, even in the absence of parental genotypes. Our strategy involves creating “virtual” mothers and fathers by estimating the genotypic dosages of parental genotypes using physically genotyped data from relative pairs. We then utilize the expected dosages of the parents, and the actual genotypes of the offspring relative pairs, to perform conditional genetic association analyses to obtain asymptotically unbiased estimates of maternal, paternal and offspring genetic effects. We develop a freely available web application that quantifies the power of our approach using closed form asymptotic solutions. We implement our methods in a user-friendly software package IMPISH (IMputing Parental genotypes In Siblings and Half-Siblings) which allows users to quickly and efficiently impute parental genotypes across the genome in large genome-wide datasets, and then use these estimated dosages in downstream linear mixed model association analyses. We conclude that imputing parental genotypes from relative pairs may provide a useful adjunct to existing large-scale genetic studies of parents and their offspring.

Mobile Software Assurance Informed through Knowledge Graph Construction: The OWASP Threat of Insecure Data Storage

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Suzanna Schmeelk ◽  
Lixin Tao
Keyword(s):  
Data Storage ◽  
Program Analysis ◽  
Web Application ◽  
Security Analysis ◽  
Knowledge Graph ◽  
Healthcare Applications ◽  
Sensitive Data ◽  
Knowledge Graphs ◽  
Mobile Malware Detection ◽  
Software Assurance

Many organizations, to save costs, are movinheg to t Bring Your Own Mobile Device (BYOD) model and adopting applications built by third-parties at an unprecedented rate.  Our research examines software assurance methodologies specifically focusing on security analysis coverage of the program analysis for mobile malware detection, mitigation, and prevention.  This research focuses on secure software development of Android applications by developing knowledge graphs for threats reported by the Open Web Application Security Project (OWASP).  OWASP maintains lists of the top ten security threats to web and mobile applications.  We develop knowledge graphs based on the two most recent top ten threat years and show how the knowledge graph relationships can be discovered in mobile application source code.  We analyze 200+ healthcare applications from GitHub to gain an understanding of their software assurance of their developed software for one of the OWASP top ten moble threats, the threat of “Insecure Data Storage.”  We find that many of the applications are storing personally identifying information (PII) in potentially vulnerable places leaving users exposed to higher risks for the loss of their sensitive data.

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