Base de dados : MEDLINE
Pesquisa : L01.224.097 [Categoria DeCS]
Referências encontradas : 228 [refinar]
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[PMID]:29352282
[Au] Autor:Liu J; Wu Z; Dong J; Wu J; Wen D
[Ad] Endereço:School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China.
[Ti] Título:An energy-efficient failure detector for vehicular cloud computing.
[So] Source:PLoS One;13(1):e0191577, 2018.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Failure detectors are one of the fundamental components for maintaining the high availability of vehicular cloud computing. In vehicular cloud computing, lots of RSUs are deployed along the road to improve the connectivity. Many of them are equipped with solar battery due to the unavailability or excess expense of wired electrical power. So it is important to reduce the battery consumption of RSU. However, the existing failure detection algorithms are not designed to save battery consumption RSU. To solve this problem, a new energy-efficient failure detector 2E-FD has been proposed specifically for vehicular cloud computing. 2E-FD does not only provide acceptable failure detection service, but also saves the battery consumption of RSU. Through the comparative experiments, the results show that our failure detector has better performance in terms of speed, accuracy and battery consumption.
[Mh] Termos MeSH primário: Computação em Nuvem
Fontes de Energia Elétrica/estatística & dados numéricos
Veículos Automotores/estatística & dados numéricos
[Mh] Termos MeSH secundário: Algoritmos
Redes de Comunicação de Computadores
Falha de Equipamento/estatística & dados numéricos
Seres Humanos
Internet
Energia Solar/estatística & dados numéricos
Integração de Sistemas
[Pt] Tipo de publicação:COMPARATIVE STUDY; EVALUATION STUDIES; JOURNAL ARTICLE; RESEARCH SUPPORT, NON-U.S. GOV'T
[Em] Mês de entrada:1802
[Cu] Atualização por classe:180226
[Lr] Data última revisão:
180226
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:180121
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0191577


  2 / 228 MEDLINE  
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[PMID]:29324744
[Au] Autor:Chiva C; Olivella R; Borràs E; Espadas G; Pastor O; Solé A; Sabidó E
[Ad] Endereço:Proteomics Unit, Centre de Regulació Genòmica (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Barcelona.
[Ti] Título:QCloud: A cloud-based quality control system for mass spectrometry-based proteomics laboratories.
[So] Source:PLoS One;13(1):e0189209, 2018.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:The increasing number of biomedical and translational applications in mass spectrometry-based proteomics poses new analytical challenges and raises the need for automated quality control systems. Despite previous efforts to set standard file formats, data processing workflows and key evaluation parameters for quality control, automated quality control systems are not yet widespread among proteomics laboratories, which limits the acquisition of high-quality results, inter-laboratory comparisons and the assessment of variability of instrumental platforms. Here we present QCloud, a cloud-based system to support proteomics laboratories in daily quality assessment using a user-friendly interface, easy setup, automated data processing and archiving, and unbiased instrument evaluation. QCloud supports the most common targeted and untargeted proteomics workflows, it accepts data formats from different vendors and it enables the annotation of acquired data and reporting incidences. A complete version of the QCloud system has successfully been developed and it is now open to the proteomics community (http://qcloud.crg.eu). QCloud system is an open source project, publicly available under a Creative Commons License Attribution-ShareAlike 4.0.
[Mh] Termos MeSH primário: Computação em Nuvem
Espectrometria de Massas/métodos
Proteômica/métodos
[Mh] Termos MeSH secundário: Controle de Qualidade
[Pt] Tipo de publicação:JOURNAL ARTICLE; RESEARCH SUPPORT, NON-U.S. GOV'T
[Em] Mês de entrada:1801
[Cu] Atualização por classe:180129
[Lr] Data última revisão:
180129
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:180112
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0189209


  3 / 228 MEDLINE  
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[PMID]:28449639
[Au] Autor:Agrawal S; Arze C; Adkins RS; Crabtree J; Riley D; Vangala M; Galens K; Fraser CM; Tettelin H; White O; Angiuoli SV; Mahurkar A; Fricke WF
[Ad] Endereço:Institute for Genome Sciences, Baltimore, MD, USA.
[Ti] Título:CloVR-Comparative: automated, cloud-enabled comparative microbial genome sequence analysis pipeline.
[So] Source:BMC Genomics;18(1):332, 2017 04 27.
[Is] ISSN:1471-2164
[Cp] País de publicação:England
[La] Idioma:eng
[Ab] Resumo:BACKGROUND: The benefit of increasing genomic sequence data to the scientific community depends on easy-to-use, scalable bioinformatics support. CloVR-Comparative combines commonly used bioinformatics tools into an intuitive, automated, and cloud-enabled analysis pipeline for comparative microbial genomics. RESULTS: CloVR-Comparative runs on annotated complete or draft genome sequences that are uploaded by the user or selected via a taxonomic tree-based user interface and downloaded from NCBI. CloVR-Comparative runs reference-free multiple whole-genome alignments to determine unique, shared and core coding sequences (CDSs) and single nucleotide polymorphisms (SNPs). Output includes short summary reports and detailed text-based results files, graphical visualizations (phylogenetic trees, circular figures), and a database file linked to the Sybil comparative genome browser. Data up- and download, pipeline configuration and monitoring, and access to Sybil are managed through CloVR-Comparative web interface. CloVR-Comparative and Sybil are distributed as part of the CloVR virtual appliance, which runs on local computers or the Amazon EC2 cloud. Representative datasets (e.g. 40 draft and complete Escherichia coli genomes) are processed in <36 h on a local desktop or at a cost of <$20 on EC2. CONCLUSIONS: CloVR-Comparative allows anybody with Internet access to run comparative genomics projects, while eliminating the need for on-site computational resources and expertise.
[Mh] Termos MeSH primário: Computação em Nuvem
Genômica/métodos
Software
[Mh] Termos MeSH secundário: Automação
Genoma Microbiano/genética
Alinhamento de Sequência
Análise de Sequência
[Pt] Tipo de publicação:COMPARATIVE STUDY; JOURNAL ARTICLE; RESEARCH SUPPORT, N.I.H., EXTRAMURAL; RESEARCH SUPPORT, U.S. GOV'T, P.H.S.
[Em] Mês de entrada:1712
[Cu] Atualização por classe:180104
[Lr] Data última revisão:
180104
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170429
[St] Status:MEDLINE
[do] DOI:10.1186/s12864-017-3717-3


  4 / 228 MEDLINE  
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[PMID]:29016652
[Au] Autor:Li Z; Yuan X; Cui X; Liu X; Wang L; Zhang W; Lu Q; Zhu H
[Ad] Endereço:College of Computer and Communication Engineering, China University of Petroleum, Qingdao 266580, Shandong, China.
[Ti] Título:Optimal experimental conditions for Welan gum production by support vector regression and adaptive genetic algorithm.
[So] Source:PLoS One;12(10):e0185942, 2017.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Welan gum is a kind of novel microbial polysaccharide, which is widely produced during the process of microbial growth and metabolism in different external conditions. Welan gum can be used as the thickener, suspending agent, emulsifier, stabilizer, lubricant, film-forming agent and adhesive usage in agriculture. In recent years, finding optimal experimental conditions to maximize the production is paid growing attentions. In this work, a hybrid computational method is proposed to optimize experimental conditions for producing Welan gum with data collected from experiments records. Support Vector Regression (SVR) is used to model the relationship between Welan gum production and experimental conditions, and then adaptive Genetic Algorithm (AGA, for short) is applied to search optimized experimental conditions. As results, a mathematic model of predicting production of Welan gum from experimental conditions is obtained, which achieves accuracy rate 88.36%. As well, a class of optimized experimental conditions is predicted for producing Welan gum 31.65g/L. Comparing the best result in chemical experiment 30.63g/L, the predicted production improves it by 3.3%. The results provide potential optimal experimental conditions to improve the production of Welan gum.
[Mh] Termos MeSH primário: Carboidratos da Dieta
Polissacarídeos Bacterianos/biossíntese
Polissacarídeos/biossíntese
[Mh] Termos MeSH secundário: Agricultura
Algoritmos
Computação em Nuvem
Mineração de Dados
Emulsificantes/química
Excipientes/química
Glucose/química
Lubrificantes/química
Polissacarídeos/química
Polissacarídeos Bacterianos/química
Máquina de Vetores de Suporte
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Nm] Nome de substância:
0 (Dietary Carbohydrates); 0 (Emulsifying Agents); 0 (Excipients); 0 (Lubricants); 0 (Polysaccharides); 0 (Polysaccharides, Bacterial); 96949-22-3 (welan); IY9XDZ35W2 (Glucose)
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171101
[Lr] Data última revisão:
171101
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:171011
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0185942


  5 / 228 MEDLINE  
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[PMID]:28953943
[Au] Autor:Midekisa A; Holl F; Savory DJ; Andrade-Pacheco R; Gething PW; Bennett A; Sturrock HJW
[Ad] Endereço:Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, California, United States of America.
[Ti] Título:Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.
[So] Source:PLoS One;12(9):e0184926, 2017.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.
[Mh] Termos MeSH primário: Computação em Nuvem
Terra (Planeta)
Sistemas de Informação Geográfica
[Mh] Termos MeSH secundário: África
Modelos Teóricos
Astronave
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171024
[Lr] Data última revisão:
171024
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170928
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0184926


  6 / 228 MEDLINE  
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[PMID]:28859125
[Au] Autor:Wang S; Zhao D; Zhang Y
[Ad] Endereço:School of Science, Xi'an University of Technology, Xi'an, Shaanxi, China.
[Ti] Título:Searchable attribute-based encryption scheme with attribute revocation in cloud storage.
[So] Source:PLoS One;12(8):e0183459, 2017.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Attribute based encryption (ABE) is a good way to achieve flexible and secure access control to data, and attribute revocation is the extension of the attribute-based encryption, and the keyword search is an indispensable part for cloud storage. The combination of both has an important application in the cloud storage. In this paper, we construct a searchable attribute-based encryption scheme with attribute revocation in cloud storage, the keyword search in our scheme is attribute based with access control, when the search succeeds, the cloud server returns the corresponding cipher text to user and the user can decrypt the cipher text definitely. Besides, our scheme supports multiple keywords search, which makes the scheme more practical. Under the assumption of decisional bilinear Diffie-Hellman exponent (q-BDHE) and decisional Diffie-Hellman (DDH) in the selective security model, we prove that our scheme is secure.
[Mh] Termos MeSH primário: Computação em Nuvem
Segurança Computacional
Armazenamento e Recuperação da Informação
[Mh] Termos MeSH secundário: Algoritmos
Confidencialidade
Registros Eletrônicos de Saúde
Troca de Informação em Saúde
Seres Humanos
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171016
[Lr] Data última revisão:
171016
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170901
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0183459


  7 / 228 MEDLINE  
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[PMID]:28692697
[Au] Autor:Pervez Z; Ahmad M; Khattak AM; Ramzan N; Khan WA
[Ad] Endereço:School of Engineering and Computing, University of the West of Scotland, Paisley, PA1 2BE, United Kingdom.
[Ti] Título:[Formula: see text]: Oblivious similarity based searching for encrypted data outsourced to an untrusted domain.
[So] Source:PLoS One;12(7):e0179720, 2017.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Public cloud storage services are becoming prevalent and myriad data sharing, archiving and collaborative services have emerged which harness the pay-as-you-go business model of public cloud. To ensure privacy and confidentiality often encrypted data is outsourced to such services, which further complicates the process of accessing relevant data by using search queries. Search over encrypted data schemes solve this problem by exploiting cryptographic primitives and secure indexing to identify outsourced data that satisfy the search criteria. Almost all of these schemes rely on exact matching between the encrypted data and search criteria. A few schemes which extend the notion of exact matching to similarity based search, lack realism as those schemes rely on trusted third parties or due to increase storage and computational complexity. In this paper we propose Oblivious Similarity based Search ([Formula: see text]) for encrypted data. It enables authorized users to model their own encrypted search queries which are resilient to typographical errors. Unlike conventional methodologies, [Formula: see text] ranks the search results by using similarity measure offering a better search experience than exact matching. It utilizes encrypted bloom filter and probabilistic homomorphic encryption to enable authorized users to access relevant data without revealing results of search query evaluation process to the untrusted cloud service provider. Encrypted bloom filter based search enables [Formula: see text] to reduce search space to potentially relevant encrypted data avoiding unnecessary computation on public cloud. The efficacy of [Formula: see text] is evaluated on Google App Engine for various bloom filter lengths on different cloud configurations.
[Mh] Termos MeSH primário: Segurança Computacional
Disseminação de Informação
Ferramenta de Busca
[Mh] Termos MeSH secundário: Algoritmos
Computação em Nuvem
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1709
[Cu] Atualização por classe:170925
[Lr] Data última revisão:
170925
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170711
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0179720


  8 / 228 MEDLINE  
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[PMID]:28655296
[Au] Autor:de Castro MR; Tostes CDS; Dávila AMR; Senger H; da Silva FAB
[Ad] Endereço:Computer Science Department, Federal University of São Carlos, Rod. Washington Luís, Km 235, São Carlos, 21040-900, Brazil.
[Ti] Título:SparkBLAST: scalable BLAST processing using in-memory operations.
[So] Source:BMC Bioinformatics;18(1):318, 2017 Jun 27.
[Is] ISSN:1471-2105
[Cp] País de publicação:England
[La] Idioma:eng
[Ab] Resumo:BACKGROUND: The demand for processing ever increasing amounts of genomic data has raised new challenges for the implementation of highly scalable and efficient computational systems. In this paper we propose SparkBLAST, a parallelization of a sequence alignment application (BLAST) that employs cloud computing for the provisioning of computational resources and Apache Spark as the coordination framework. As a proof of concept, some radionuclide-resistant bacterial genomes were selected for similarity analysis. RESULTS: Experiments in Google and Microsoft Azure clouds demonstrated that SparkBLAST outperforms an equivalent system implemented on Hadoop in terms of speedup and execution times. CONCLUSIONS: The superior performance of SparkBLAST is mainly due to the in-memory operations available through the Spark framework, consequently reducing the number of local I/O operations required for distributed BLAST processing.
[Mh] Termos MeSH primário: Software
[Mh] Termos MeSH secundário: Algoritmos
Computação em Nuvem
Hibridização Genômica Comparativa
Bases de Dados Factuais
Alinhamento de Sequência
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1711
[Cu] Atualização por classe:171107
[Lr] Data última revisão:
171107
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170629
[St] Status:MEDLINE
[do] DOI:10.1186/s12859-017-1723-8


  9 / 228 MEDLINE  
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[PMID]:28640285
[Ti] Título:Don't let Europe's open-science dream drift.
[So] Source:Nature;546(7659):451, 2017 06 20.
[Is] ISSN:1476-4687
[Cp] País de publicação:England
[La] Idioma:eng
[Mh] Termos MeSH primário: Computação em Nuvem
Disseminação de Informação/métodos
Armazenamento e Recuperação da Informação/métodos
Cooperação Internacional
Internet
Publicação de Acesso Aberto/tendências
Ciência/organização & administração
[Mh] Termos MeSH secundário: Computação em Nuvem/economia
Computação em Nuvem/tendências
Europa (Continente)
Armazenamento e Recuperação da Informação/economia
Armazenamento e Recuperação da Informação/tendências
Comunicação Interdisciplinar
Publicação de Acesso Aberto/economia
Reprodutibilidade dos Testes
Ciência/economia
[Pt] Tipo de publicação:EDITORIAL
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171019
[Lr] Data última revisão:
171019
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170623
[St] Status:MEDLINE
[do] DOI:10.1038/546451a


  10 / 228 MEDLINE  
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[PMID]:28633659
[Au] Autor:Molnár-Gábor F; Lueck R; Yakneen S; Korbel JO
[Ad] Endereço:Heidelberg Academy of Sciences and Humanities, Karlstraße 4, 69117, Heidelberg, Germany. Fruzsina.Molnar-Gabor@adw.uni-heidelberg.de.
[Ti] Título:Computing patient data in the cloud: practical and legal considerations for genetics and genomics research in Europe and internationally.
[So] Source:Genome Med;9(1):58, 2017 Jun 20.
[Is] ISSN:1756-994X
[Cp] País de publicação:England
[La] Idioma:eng
[Ab] Resumo:Biomedical research is becoming increasingly large-scale and international. Cloud computing enables the comprehensive integration of genomic and clinical data, and the global sharing and collaborative processing of these data within a flexibly scalable infrastructure. Clouds offer novel research opportunities in genomics, as they facilitate cohort studies to be carried out at unprecedented scale, and they enable computer processing with superior pace and throughput, allowing researchers to address questions that could not be addressed by studies using limited cohorts. A well-developed example of such research is the Pan-Cancer Analysis of Whole Genomes project, which involves the analysis of petabyte-scale genomic datasets from research centers in different locations or countries and different jurisdictions. Aside from the tremendous opportunities, there are also concerns regarding the utilization of clouds; these concerns pertain to perceived limitations in data security and protection, and the need for due consideration of the rights of patient donors and research participants. Furthermore, the increased outsourcing of information technology impedes the ability of researchers to act within the realm of existing local regulations owing to fundamental differences in the understanding of the right to data protection in various legal systems. In this Opinion article, we address the current opportunities and limitations of cloud computing and highlight the responsible use of federated and hybrid clouds that are set up between public and private partners as an adequate solution for genetics and genomics research in Europe, and under certain conditions between Europe and international partners. This approach could represent a sensible middle ground between fragmented individual solutions and a "one-size-fits-all" approach.
[Mh] Termos MeSH primário: Pesquisa Biomédica
Computação em Nuvem/legislação & jurisprudência
Segurança Computacional/legislação & jurisprudência
Genômica
[Mh] Termos MeSH secundário: Europa (Continente)
Seres Humanos
[Pt] Tipo de publicação:JOURNAL ARTICLE; REVIEW
[Em] Mês de entrada:1709
[Cu] Atualização por classe:170901
[Lr] Data última revisão:
170901
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170622
[St] Status:MEDLINE
[do] DOI:10.1186/s13073-017-0449-6



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