Base de dados : MEDLINE
Pesquisa : L01.313 [Categoria DeCS]
Referências encontradas : 831 [refinar]
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  1 / 831 MEDLINE  
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[PMID]:29357800
[Au] Autor:Siverio-Mota D; Andujar I; Marrero-Ponce Y; Giner RM; Diaz-Mendoza C; Paba GM; Vicet-Muro L; Cordero-Maldonado ML; de Witte PAM; Crawford AD; Veitia MS; Perez-Jimenez F; Aran VJ
[Ad] Endereço:Laboratory for Molecular Biodiscovery, Department of Pharmaceutical and Pharmacological Sciences, University of Leuven, Herestraat 49, 3000 Leuven, Belgium.
[Ti] Título:Anti-Inflammatory Activity and Cheminformatics Analysis of New Poten t 2-Substituted 1-Methyl-5-Nitroindazolinones.
[So] Source:Curr Top Med Chem;17(30):3236-3248, 2018 Feb 09.
[Is] ISSN:1873-4294
[Cp] País de publicação:Netherlands
[La] Idioma:eng
[Ab] Resumo:After the identification of the anti-inflammatory properties of VA5-13l (2-benzyl-1- methyl-5-nitroindazolinone) in previous investigations, some of its analogous compounds were designed, synthesized and evaluated in two anti-inflammatory methods: LPS-enhanced leukocyte migration assay in zebrafish; and 12-O-tetradecanoylphorbol-13-acetate (TPA)-induced mouse ear edema. The products evaluated (3, 6, 8, 9 and 10) showed the lower values of relative leukocyte migration at 30 µM (0.14, 0.07, 0.10, 0.13 and 0.07, respectively), while in ear edema and myeloperoxidase activity methods, all the compounds reduced inflammation, only 4 and 16 yielded unsatisfactory results. The relationship linking structure and activity (SAR analysis) was determinate by using SARANEA software. The importance of the 5-Nitro group of the indazole ring for the activity was evident, and showed modest reduction when benzyl (Bn) is changed by alkyl group. A substituted Bn moiety at N2 (R) is the best substituent (5-10); nevertheless, if methylene group of Bn is deleted, the activity is affected. Also, introduction of halogen atoms mainly at positions 3 or 4 of the benzyl moiety (6 and 10) leads in general to strong activities. In fact, compounds 7 and 8 (R = 4-FBn or 4-ClBn, respectively) exhibit satisfactory results in in vivo tests and appear promising. The production of IL-6 at all doses assayed was significantly reduced, except with 16. Nonetheless, the production of TNF-α was significantly inhibited only by this chemical (16) at concentration of 50 µM. On the other hand, compound 2 was the one that mostly inhibited the expression of COX-2 and iNOS. From these results, it can be concluded that the inhibition in the release of cytokines can be one of the mechanisms of action responsible for the anti-inflammatory effect for 2-benzyl derivates while other 2-alkyl derivatives can inhibit production of NO. Therefore, nitroindazolinone chemical prototype could be an interesting structural group with anti-inflammatory purposes in the therapeutic.
[Mh] Termos MeSH primário: Anti-Inflamatórios não Esteroides/farmacologia
Inibidores de Ciclo-Oxigenase 2/farmacologia
Indazóis/farmacologia
Informática
Nitrocompostos/farmacologia
[Mh] Termos MeSH secundário: Animais
Anti-Inflamatórios não Esteroides/química
Ciclo-Oxigenase 2/metabolismo
Inibidores de Ciclo-Oxigenase 2/química
Relação Dose-Resposta a Droga
Seres Humanos
Indazóis/química
Lipopolissacarídeos/antagonistas & inibidores
Lipopolissacarídeos/farmacologia
Estrutura Molecular
Óxido Nítrico/antagonistas & inibidores
Óxido Nítrico/biossíntese
Óxido Nítrico Sintase Tipo II/antagonistas & inibidores
Óxido Nítrico Sintase Tipo II/metabolismo
Nitrocompostos/química
Relação Estrutura-Atividade
Fator de Necrose Tumoral alfa/antagonistas & inibidores
Peixe-Zebra
[Pt] Tipo de publicação:JOURNAL ARTICLE; REVIEW
[Nm] Nome de substância:
0 (Anti-Inflammatory Agents, Non-Steroidal); 0 (Cyclooxygenase 2 Inhibitors); 0 (Indazoles); 0 (Lipopolysaccharides); 0 (Nitro Compounds); 0 (Tumor Necrosis Factor-alpha); 31C4KY9ESH (Nitric Oxide); EC 1.14.13.39 (Nitric Oxide Synthase Type II); EC 1.14.99.1 (Cyclooxygenase 2)
[Em] Mês de entrada:1803
[Cu] Atualização por classe:180308
[Lr] Data última revisão:
180308
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:180124
[St] Status:MEDLINE
[do] DOI:10.2174/1568026618666180119125255


  2 / 831 MEDLINE  
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[PMID]:28970618
[Au] Autor:Beckett RD; Etheridge K; DeLellis T
[Ad] Endereço:Manchester University College of Pharmacy, Natural and Health Sciences, Fort Wayne, Indiana.
[Ti] Título:A Team, Case-based Examination and Its Impact on Student Performance in a Patient Safety and Informatics Course.
[So] Source:Am J Pharm Educ;81(6):117, 2017 Aug.
[Is] ISSN:1553-6467
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:To describe the redesigned assessment plan for a patient safety and informatics course and assess student pharmacist performance and perceptions. The final examination of a patient safety course was redesigned from traditional multiple choice and short answer to team-based, open-ended, and case-based. Faculty for each class session developed higher level activities, focused on developing key skills or attitudes deemed essential for practice, for a progressive patient case consisting of nine activities. Student performance and perceptions were analyzed with pre- and post-surveys using 5-point scales. Mean performance on the examination was 93.6%; median scores for each assessed course outcome ranged from 90% to 100%. Eighty-five percent of students completed both surveys. Confidence performing skills and demonstrating attitudes improved for each item on post-survey compared with pre-survey. Eighty-one percent of students indicated the experience of taking the examination was beneficial for their professional development. A team, case-based examination was associated with high student performance and improved self-confidence in performing medication safety-related skills.
[Mh] Termos MeSH primário: Educação em Farmácia
Avaliação Educacional/métodos
Informática/educação
Segurança do Paciente
Autoimagem
Estudantes de Farmácia
[Mh] Termos MeSH secundário: Adulto
Currículo
Avaliação Educacional/normas
Feminino
Seres Humanos
Masculino
Meia-Idade
Estudantes de Farmácia/psicologia
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1711
[Cu] Atualização por classe:171101
[Lr] Data última revisão:
171101
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:171004
[St] Status:MEDLINE
[do] DOI:10.5688/ajpe816117


  3 / 831 MEDLINE  
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[PMID]:28934352
[Au] Autor:Bragazzi NL; Alicino C; Trucchi C; Paganino C; Barberis I; Martini M; Sticchi L; Trinka E; Brigo F; Ansaldi F; Icardi G; Orsi A
[Ad] Endereço:Department of Health Sciences, University of Genoa, Genoa, Italy.
[Ti] Título:Global reaction to the recent outbreaks of Zika virus: Insights from a Big Data analysis.
[So] Source:PLoS One;12(9):e0185263, 2017.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:OBJECTIVE: The recent spreading of Zika virus represents an emerging global health threat. As such, it is attracting public interest worldwide, generating a great amount of related Internet searches and social media interactions. The aim of this research was to understand Zika-related digital behavior throughout the epidemic spreading and to assess its consistence with real-world epidemiological data, using a behavioral informatics and analytics approach. METHODS: In this study, the global web-interest and reaction to the recently occurred outbreaks of the Zika Virus were analyzed in terms of tweets and Google Trends (GT), Google News, YouTube, and Wikipedia search queries. These data streams were mined from 1st January 2004 to 31st October 2016, with a focus on the period November 2015-October 2016. This analysis was complemented with the use of epidemiological data. Spearman's correlation was performed to correlate all Zika-related data. Moreover, a multivariate regression was performed using Zika-related search queries as a dependent variable, and epidemiological data, number of inhabitants in 2015 and Human Development Index as predictor variables. RESULTS: Overall 3,864,395 tweets, 284,903 accesses to Wikipedia pages dedicated to the Zika virus were analyzed during the study period. All web-data sources showed that the main spike of researches and interactions occurred in February 2016 with a second peak in August 2016. All novel data streams-related activities increased markedly during the epidemic period with respect to pre-epidemic period when no web activity was detected. Correlations between data from all these web platforms resulted very high and statistically significant. The countries in which web searches were particularly concentrated are mainly from Central and South Americas. The majority of queries concerned the symptoms of the Zika virus, its vector of transmission, and its possible effect to babies, including microcephaly. No statistically significant correlation was found between novel data streams and global real-world epidemiological data. At country level, a correlation between the digital interest towards the Zika virus and Zika incidence rate or microcephaly cases has been detected. CONCLUSIONS: An increasing public interest and reaction to the current Zika virus outbreak was documented by all web-data sources and a similar pattern of web reactions has been detected. The public opinion seems to be particularly worried by the alert of teratogenicity of the Zika virus. Stakeholders and health authorities could usefully exploited these internet tools for collecting the concerns of public opinion and reply to them, disseminating key information.
[Mh] Termos MeSH primário: Surtos de Doenças
Informática
Internacionalidade
Infecção pelo Zika virus/epidemiologia
Zika virus/fisiologia
[Mh] Termos MeSH secundário: Seres Humanos
Internet
Mídias Sociais
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171018
[Lr] Data última revisão:
171018
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170922
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0185263


  4 / 831 MEDLINE  
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[PMID]:28886072
[Au] Autor:Marangu D; Mwaniki H; Nduku S; Maleche-Obimbo E; Jaoko W; Babigumira J; John-Stewart G; Rao D
[Ad] Endereço:Department of Paediatrics and Child Health, University of Nairobi, Nairobi, Kenya.
[Ti] Título:Stakeholder perspectives for optimization of tuberculosis contact investigation in a high-burden setting.
[So] Source:PLoS One;12(9):e0183749, 2017.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:INTRODUCTION: Optimal tuberculosis contact investigation impacts TB prevention, timely case finding and linkage to care, however data on routine implementation in high burden contexts is limited. MATERIALS AND METHODS: In a multi-method qualitative study based on individual interviews with TB patients, facility observations and focus group discussions with health workers (HWs) in 13 public health facilities, and key informant interviews with governmental and non-governmental experts, we describe TB contact investigation in the context of an urban setting in Kenya and identify opportunities for optimization. RESULTS: Invitation of TB patients to bring close contacts by HWs was key for all patient decisions that led to contact screening in addition to patients' understanding of TB transmission and desire to avoid contacts suffering from TB. Sub-optimal HW enquiry of TB patients and contacts presenting at the facility were missed opportunities which stemmed from lack of standardized operational procedures, documentation tools and HW training. Stakeholders proposed provision of fast tracked and holistic health packages for contacts seeking TB screening, and sustainable government led funding for the requisite infrastructure and workforce. CONCLUSION: TB contact invitation by HWs leading to contact screening occurs in this context. Stakeholder perspectives inform the design of an operational framework for optimized delivery.
[Mh] Termos MeSH primário: Tuberculose/transmissão
[Mh] Termos MeSH secundário: Adulto
Feminino
Pessoal de Saúde
Seres Humanos
Informática
Quênia/epidemiologia
Masculino
Meia-Idade
Tuberculose/epidemiologia
Adulto Jovem
[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:170909
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0183749


  5 / 831 MEDLINE  
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[PMID]:28812890
[Au] Autor:Chomenidis C; Drakakis G; Tsiliki G; Anagnostopoulou E; Valsamis A; Doganis P; Sopasakis P; Sarimveis H
[Ad] Endereço:School of Chemical Engineering, National Technical University of Athens , Heroon Polytechneiou 9, Zografou, Athens, Greece.
[Ti] Título:Jaqpot Quattro: A Novel Computational Web Platform for Modeling and Analysis in Nanoinformatics.
[So] Source:J Chem Inf Model;57(9):2161-2172, 2017 Sep 25.
[Is] ISSN:1549-960X
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Engineered nanomaterials (ENMs) are increasingly infiltrating our lives as a result of their applications across multiple fields. However, ENM formulations may result in the modulation of pathways and mechanisms of toxic action that endanger human health and the environment. Alternative testing methods such as in silico approaches are becoming increasingly popular for assessing the safety of ENMs, as they are cost- and time-effective. Additionally, computational approaches support the industrial safer-by-design challenge and the REACH legislation objective of reducing animal testing. Because of the novelty of the field, there is also an evident need for harmonization in terms of databases, ontology, and modeling infrastructures. To this end, we present Jaqpot Quattro, a comprehensive open-source web application for ENM modeling with emphasis on predicting adverse effects of ENMs. We describe the system architecture and outline the functionalities, which include nanoQSAR modeling, validation services, read-across predictions, optimal experimental design, and interlaboratory testing.
[Mh] Termos MeSH primário: Informática/métodos
Internet
Nanoestruturas/efeitos adversos
[Mh] Termos MeSH secundário: Engenharia
Nanoestruturas/química
Relação Estrutura-Atividade
Interface Usuário-Computador
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171010
[Lr] Data última revisão:
171010
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170817
[St] Status:MEDLINE
[do] DOI:10.1021/acs.jcim.7b00223


  6 / 831 MEDLINE  
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[PMID]:28810125
[Au] Autor:Varela JN; Lammoglia Cobo MF; Pawar SV; Yadav VG
[Ad] Endereço:Department of Chemical & Biological Engineering, The University of British Columbia , Vancouver, BC, Canada , V6T 1Z3.
[Ti] Título:Cheminformatic Analysis of Antimalarial Chemical Space Illuminates Therapeutic Mechanisms and Offers Strategies for Therapy Development.
[So] Source:J Chem Inf Model;57(9):2119-2131, 2017 Sep 25.
[Is] ISSN:1549-960X
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:The clear and present danger of malaria, which has been amplified in recent years by climate change, and the progressive thinning of our drug arsenal over the past two decades raise uncomfortable questions about the current state and future of antimalarial drug development. Besides suffering from many of the same technical challenges that affect drug development in other disease areas, the quest for new antimalarial therapies is also hindered by the complex, dynamic life cycle of the malaria parasite, P. falciparum, in its mosquito and human hosts, and its role thereof in the elicitation of drug resistance. New strategies are needed in order to ensure economical and expeditious development of new, more efficacious treatments. In the present study, we employ open-source cheminformatics tools to analyze the chemical space traversed by approved antimalarial drugs and promising candidates at various stages of development to uncover insights that could shape future endeavors in the field. Our scaffold-centric analysis reveals that the antimalarial chemical space is disjointed and segregated into a few dominant structural groups. In fact, the structures of antimalarial drugs and drug candidates are distributed according to Pareto's principle. This structural convergence can potentially be exploited for future drug discovery by incorporating it into bioinformatics workflows that are typically employed for solving problems in structural biology. Significantly, we demonstrate how molecular scaffold hunting can be applied to unearth putative mechanisms of action of drugs whose activities remain a mystery, and how scaffold-centric analysis of drug space can also provide a recipe for combination therapies that minimize the likelihood of emergence of drug resistance, as well as identify areas on which to focus efforts. Finally, we also observe that over half of the molecules in the antimalarial space bear no resemblance to other molecules in the collection, which suggests that the pharmacobiology of antimalarial drugs has not been entirely surveyed.
[Mh] Termos MeSH primário: Antimaláricos/farmacologia
Descoberta de Drogas/métodos
Informática/métodos
Malária Falciparum/tratamento farmacológico
[Mh] Termos MeSH secundário: Antimaláricos/química
Antimaláricos/uso terapêutico
Resistência a Medicamentos
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Nm] Nome de substância:
0 (Antimalarials)
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171010
[Lr] Data última revisão:
171010
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170816
[St] Status:MEDLINE
[do] DOI:10.1021/acs.jcim.7b00072


  7 / 831 MEDLINE  
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[PMID]:28737911
[Au] Autor:González-Medina M; Medina-Franco JL
[Ad] Endereço:School of Chemistry, Department of Pharmacy, Universidad Nacional Autónoma de México , Avenida Universidad 3000, Mexico City 04510, Mexico.
[Ti] Título:Platform for Unified Molecular Analysis: PUMA.
[So] Source:J Chem Inf Model;57(8):1735-1740, 2017 Aug 28.
[Is] ISSN:1549-960X
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:We introduce a free platform for chemoinformatic-based diversity analysis and visualization of chemical space of user supplied data sets. Platform for Unified Molecular Analysis (PUMA) integrates metrics used to characterize compound databases including visualization of chemical space, scaffold content, and analysis of chemical diversity. The user's input is a file with SMILES, database names, and compound IDs. PUMA computes molecular properties of pharmaceutical relevance, Murcko scaffolds, and diversity analysis. The user can interactively navigate through the graphs and export image files and the raw data of the diversity calculations. The platform links two public online resources: Consensus Diversity Plots for the assessment of global diversity and Activity Landscape Plotter to analyze structure-activity relationships. Herein, we describe the functionalities of PUMA and exemplify its use through the analysis of compound databases of general interest. PUMA is freely accessible at the authors web-site https://www.difacquim.com/d-tools/ .
[Mh] Termos MeSH primário: Bases de Dados de Produtos Farmacêuticos
Informática/métodos
Software
[Mh] Termos MeSH secundário: Gráficos por Computador
Internet
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171002
[Lr] Data última revisão:
171002
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170725
[St] Status:MEDLINE
[do] DOI:10.1021/acs.jcim.7b00253


  8 / 831 MEDLINE  
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[PMID]:28727421
[Au] Autor:Rensi SE; Altman RB
[Ad] Endereço:Department of Bioengineering, Stanford University , Shriram Center, Room 213, 443 Via Ortega MC 4245, Stanford, California 94305, United States.
[Ti] Título:Shallow Representation Learning via Kernel PCA Improves QSAR Modelability.
[So] Source:J Chem Inf Model;57(8):1859-1867, 2017 Aug 28.
[Is] ISSN:1549-960X
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Linear models offer a robust, flexible, and computationally efficient set of tools for modeling quantitative structure-activity relationships (QSARs) but have been eclipsed in performance by nonlinear methods. Support vector machines (SVMs) and neural networks are currently among the most popular and accurate QSAR methods because they learn new representations of the data that greatly improve modelability. In this work, we use shallow representation learning to improve the accuracy of L1 regularized logistic regression (LASSO) and meet the performance of Tanimoto SVM. We embedded chemical fingerprints in Euclidean space using Tanimoto (a.k.a. Jaccard) similarity kernel principal component analysis (KPCA) and compared the effects on LASSO and SVM model performance for predicting the binding activities of chemical compounds against 102 virtual screening targets. We observed similar performance and patterns of improvement for LASSO and SVM. We also empirically measured model training and cross-validation times to show that KPCA used in concert with LASSO classification is significantly faster than linear SVM over a wide range of training set sizes. Our work shows that powerful linear QSAR methods can match nonlinear methods and demonstrates a modular approach to nonlinear classification that greatly enhances QSAR model prototyping facility, flexibility, and transferability.
[Mh] Termos MeSH primário: Informática/métodos
Análise de Componente Principal
Relação Quantitativa Estrutura-Atividade
Máquina de Vetores de Suporte
[Mh] Termos MeSH secundário: Fatores de Tempo
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171002
[Lr] Data última revisão:
171002
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170721
[St] Status:MEDLINE
[do] DOI:10.1021/acs.jcim.6b00694


  9 / 831 MEDLINE  
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[PMID]:28715209
[Au] Autor:Marchese Robinson RL; Palczewska A; Palczewski J; Kidley N
[Ad] Endereço:Syngenta Ltd., Jealott's Hill International Research Centre , Bracknell, Berkshire RG42 6EY, United Kingdom.
[Ti] Título:Comparison of the Predictive Performance and Interpretability of Random Forest and Linear Models on Benchmark Data Sets.
[So] Source:J Chem Inf Model;57(8):1773-1792, 2017 Aug 28.
[Is] ISSN:1549-960X
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:The ability to interpret the predictions made by quantitative structure-activity relationships (QSARs) offers a number of advantages. While QSARs built using nonlinear modeling approaches, such as the popular Random Forest algorithm, might sometimes be more predictive than those built using linear modeling approaches, their predictions have been perceived as difficult to interpret. However, a growing number of approaches have been proposed for interpreting nonlinear QSAR models in general and Random Forest in particular. In the current work, we compare the performance of Random Forest to those of two widely used linear modeling approaches: linear Support Vector Machines (SVMs) (or Support Vector Regression (SVR)) and partial least-squares (PLS). We compare their performance in terms of their predictivity as well as the chemical interpretability of the predictions using novel scoring schemes for assessing heat map images of substructural contributions. We critically assess different approaches for interpreting Random Forest models as well as for obtaining predictions from the forest. We assess the models on a large number of widely employed public-domain benchmark data sets corresponding to regression and binary classification problems of relevance to hit identification and toxicology. We conclude that Random Forest typically yields comparable or possibly better predictive performance than the linear modeling approaches and that its predictions may also be interpreted in a chemically and biologically meaningful way. In contrast to earlier work looking at interpretation of nonlinear QSAR models, we directly compare two methodologically distinct approaches for interpreting Random Forest models. The approaches for interpreting Random Forest assessed in our article were implemented using open-source programs that we have made available to the community. These programs are the rfFC package ( https://r-forge.r-project.org/R/?group_id=1725 ) for the R statistical programming language and the Python program HeatMapWrapper [ https://doi.org/10.5281/zenodo.495163 ] for heat map generation.
[Mh] Termos MeSH primário: Informática/métodos
Relação Quantitativa Estrutura-Atividade
[Mh] Termos MeSH secundário: Benchmarking
Temperatura Alta
Análise dos Mínimos Quadrados
Modelos Lineares
Modelos Moleculares
Conformação Molecular
Máquina de Vetores de Suporte
[Pt] Tipo de publicação:COMPARATIVE STUDY; JOURNAL ARTICLE
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171002
[Lr] Data última revisão:
171002
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170718
[St] Status:MEDLINE
[do] DOI:10.1021/acs.jcim.6b00753


  10 / 831 MEDLINE  
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[PMID]:28696688
[Au] Autor:Coley CW; Barzilay R; Green WH; Jaakkola TS; Jensen KF
[Ad] Endereço:Department of Chemical Engineering, Massachusetts Institute of Technology , 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.
[Ti] Título:Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction.
[So] Source:J Chem Inf Model;57(8):1757-1772, 2017 Aug 28.
[Is] ISSN:1549-960X
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:The task of learning an expressive molecular representation is central to developing quantitative structure-activity and property relationships. Traditional approaches rely on group additivity rules, empirical measurements or parameters, or generation of thousands of descriptors. In this paper, we employ a convolutional neural network for this embedding task by treating molecules as undirected graphs with attributed nodes and edges. Simple atom and bond attributes are used to construct atom-specific feature vectors that take into account the local chemical environment using different neighborhood radii. By working directly with the full molecular graph, there is a greater opportunity for models to identify important features relevant to a prediction task. Unlike other graph-based approaches, our atom featurization preserves molecule-level spatial information that significantly enhances model performance. Our models learn to identify important features of atom clusters for the prediction of aqueous solubility, octanol solubility, melting point, and toxicity. Extensions and limitations of this strategy are discussed.
[Mh] Termos MeSH primário: Gráficos por Computador
Informática/métodos
Redes Neurais (Computação)
Fenômenos Físicos
[Mh] Termos MeSH secundário: Octanóis/química
Solubilidade
Testes de Toxicidade
Temperatura de Transição
Água/química
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Nm] Nome de substância:
0 (Octanols); 059QF0KO0R (Water)
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171002
[Lr] Data última revisão:
171002
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170712
[St] Status:MEDLINE
[do] DOI:10.1021/acs.jcim.6b00601



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BIREME/OPAS/OMS - Centro Latino-Americano e do Caribe de Informação em Ciências da Saúde