We discuss the application of quantitatively accurate computational methods to the study of laser-driven two-electron atoms in short intense laser pulses. The fundamental importance of such calculations to the subject...
详细信息
We discuss the application of quantitatively accurate computational methods to the study of laser-driven two-electron atoms in short intense laser pulses. The fundamental importance of such calculations to the subject area is emphasized. Calculations of single- and double-electron ionization rates at 390 nm are presented. (C) 2001 Optical Society of America.
作者：
Balaras, CANational Observatory of Athens
Institute of Meteorology and Physics of the Atmospheric Environment Group Energy Conservation PO Box 20048 GR 118 10 Athens Greece
Thermal mass can reduce peak cooling loads and indoor air temperature swings in buildings. The factors affecting the performance of thermal mass are reviewed and classified. Experimental studies which demonstrate the ...
详细信息
Thermal mass can reduce peak cooling loads and indoor air temperature swings in buildings. The factors affecting the performance of thermal mass are reviewed and classified. Experimental studies which demonstrate the effectiveness of thermal mass as an energy conservation alternative and in providing more comfortable indoor conditions, are also reviewed. A number of simplified design tools for calculating the cooling load and indoor air temperatures of a building, which also account for thermal mass effects, have been identified and are classified. The models are categorized in terms of their inputs, outputs and restrictions on their level of accuracy in treating thermal mass effects, type of loads or other design limitations.
Nuclear receptors (NRs) are important targets for therapeutic drugs. NRs regulate transcriptional activities through binding to ligands and interacting with several regulating proteins. computational methods can provi...
详细信息
Nuclear receptors (NRs) are important targets for therapeutic drugs. NRs regulate transcriptional activities through binding to ligands and interacting with several regulating proteins. computational methods can provide insights into essential ligand-receptor and protein-protein interactions. These in turn have facilitated the discovery of novel agonists and antagonists with high affinity and specificity as well as have aided in the prediction of toxic side effects of drugs by identifying possible off-target interactions. Here, we review the application of computational methods toward several clinically important NRs (with special emphasis on PXR) and discuss their use for screening and predicting the toxic side effects of xenobiotics.
Background A Generalized Linear Mixed Model (GLMM) is recommended to meta-analyze diagnostic test accuracy studies (DTAs) based on aggregate or individual participant data. Since a GLMM does not have a closed-form lik...
详细信息
Background A Generalized Linear Mixed Model (GLMM) is recommended to meta-analyze diagnostic test accuracy studies (DTAs) based on aggregate or individual participant data. Since a GLMM does not have a closed-form likelihood function or parameter solutions, computational methods are conventionally used to approximate the likelihoods and obtain parameter estimates. The most commonly used computational methods are the Iteratively Reweighted Least Squares (IRLS), the Laplace approximation (LA), and the Adaptive Gauss-Hermite quadrature (AGHQ). Despite being widely used, it has not been clear how these computational methods compare and perform in the context of an aggregate data meta-analysis (ADMA) of *** We compared and evaluated the performance of three commonly used computational methods for GLMM - the IRLS, the LA, and the AGHQ, via a comprehensive simulation study and real-life data examples, in the context of an ADMA of DTAs. By varying several parameters in our simulations, we assessed the performance of the three methods in terms of bias, root mean squared error, confidence interval (CI) width, coverage of the 95% CI, convergence rate, and computational *** For most of the scenarios, especially when the meta-analytic data were not sparse (i.e., there were no or negligible studies with perfect diagnosis), the three computational methods were comparable for the estimation of sensitivity and specificity. However, the LA had the largest bias and root mean squared error for pooled sensitivity and specificity when the meta-analytic data were sparse. Moreover, the AGHQ took a longer computational time to converge relative to the other two methods, although it had the best convergence *** We recommend practitioners and researchers carefully choose an appropriate computational algorithm when fitting a GLMM to an ADMA of DTAs. We do not recommend the LA for sparse meta-analytic data sets. However, either the AGHQ or the IRLS can be used re
Essential genes have attracted increasing attention in recent years due to the important functions of these genes in organisms. Among the methods used to identify the essential genes, accurate and efficient computatio...
详细信息
Essential genes have attracted increasing attention in recent years due to the important functions of these genes in organisms. Among the methods used to identify the essential genes, accurate and efficient computational methods can make up for the deficiencies of expensive and time-consuming experimental technologies. In this review, we have collected researches on essential gene predictions in prokaryotes and eukaryotes and summarized the five predominant types of features used in these studies. The five types of features include evolutionary conservation, domain information, network topology, sequence component and expression level. We have described how to implement the useful forms of these features and evaluated their performance based on the data of Escherichia coli MG1655, Bacillus subtilis 168 and human. The prerequisite and applicable range of these features is described. In addition, we have investigated the techniques used to weight features in various models. To facilitate researchers in the field, two available online tools, which are accessible for free and can be directly used to predict gene essentiality in prokaryotes and humans, were referred. This article provides a simple guide for the identification of essential genes in prokaryotes and eukaryotes.
computational approaches for drug discovery such as ligand-based and structure-based methods, are increasingly seen as an efficient approach for lead discovery as well as providing insights on absorption, distribution...
详细信息
computational approaches for drug discovery such as ligand-based and structure-based methods, are increasingly seen as an efficient approach for lead discovery as well as providing insights on absorption, distribution, metabolism, excretion and toxicity (ADME/Tox). What is perhaps less well known and widely described are the limitations of the different technologies. We have therefore presented a troubleshooting approach to QSAR, homology modeling, docking as well as hybrid methods. If such computational or cheminformatics methods are to become more widely used by non-experts it is critical that such limitations are brought to the user's attention and addressed during their workflows. This could improve the quality of the models and results that are obtained. (C) 2010 Elsevier Inc. All rights reserved.
Objective: To explore effective combinations of computational methods for the prediction of movement intention preceding the production of self-paced right and left hand movements from single trial scalp electroenceph...
详细信息
Objective: To explore effective combinations of computational methods for the prediction of movement intention preceding the production of self-paced right and left hand movements from single trial scalp electroencephalogram (EEG). methods: Twelve naive subjects performed self-paced movements consisting of three key strokes with either hand. EEG was recorded from 128 channels. The exploration was performed offline on single trial EEG data. We proposed that a successful computational procedure for classification would consist of spatial filtering, temporal filtering, feature selection, and pattern classification. A systematic investigation was performed with combinations of spatial filtering using principal component analysis (PCA), independent component analysis (ICA), common spatial patterns analysis (CSP), and surface Laplacian derivation (SLD);temporal filtering using power spectral density estimation (PSD) and discrete wavelet transform (DWT);pattern classification using linear Mahalanobis distance classifier (LMD), quadratic Mahalanobis distance classifier (QMD), Bayesian classifier (BSC), multi-layer perceptron neural network (MLP), probabilistic neural network (PNN), and support vector machine (SVM). A robust multivariate feature selection strategy using a genetic algorithm was employed. Results: The combinations of spatial filtering using ICA and SLD, temporal filtering using PSD and DWT, and classification methods using LMD, QMD, BSC and SVM provided higher performance than those of other combinations. Utilizing one of the better combinations of ICA, PSD and SVM, the discrimination accuracy was as high as 75%. Further feature analysis showed that beta band EEG activity of the channels over right sensorimotor cortex was most appropriate for discrimination of right and left hand movement intention. Conclusions: Effective combinations of computational methods provide possible classification of human movement intention from single trial EEG. Such a method could
Benzodiazepine receptor (BDZR) ligands are structurally diverse compounds that bind to specific binding sites on GABA(A) receptors and allosterically modulate the effect of GABA on chloride ion flux. The binding of BD...
详细信息
Benzodiazepine receptor (BDZR) ligands are structurally diverse compounds that bind to specific binding sites on GABA(A) receptors and allosterically modulate the effect of GABA on chloride ion flux. The binding of BDZR ligands to this receptor system results in activity at multiple behavioral endpoints, including anxiolytic, sedative, anticonvulsant, and hyperphagic effects. in the work presented here, a computational procedure developed in our laboratory has been used to obtain a 3D pharmacophore for ligand recognition of the GABA(A)/BDZRs initiating the hyperphagic response. To accomplish this goal, 17 structurally diverse compounds, previously assessed in our laboratory for activity at the hyperphagic endpoint, were used. The result is a four-component 3D pharmacophore. It consists of two proton acceptor atoms, the centroid of an aromatic ring and the centroid of a hydrophobic moiety in a common geometric arrangement in all compounds with activity at this endpoint. This 3D pharmacophore was then assessed and successfully validated using three different tests. First, two BDZR ligands, which were included as negative controls in the set of seventeen compounds used for the pharmacophore development, did not fit the pharmacophore. Second, some benzodiazepine ligands known to have activity at the hyperphagia endpoint, but not included in the pharmacophore development, were used as positive controls and were found to fit the pharmacophore. Finally, using the 3D pharmacophore developed in the present work to search 3D databases, over 50 classical benzodiazepines were found. Among them, were benzodiazepine ligands known to have an effect at the hyperphagic endpoint. In addition, the novel compounds also found in this search are promising therapeutic agents that could beneficially affect feeding behavior.
Novel computational methods for understanding relationships between ligands and all possible biological targets have emerged in recent years. Proteins are connected to each other based on the similarity of their ligan...
详细信息
Novel computational methods for understanding relationships between ligands and all possible biological targets have emerged in recent years. Proteins are connected to each other based on the similarity of their ligands or based on the similarity of their binding sites. The assumption is that compounds sharing chemical similarity should share targets and that targets with a similar binding site should also share ligands. A large number of computational techniques have been developed to assess ligand and binding site similarity, which can be used to mike quantitative predictions of the most probable biological target of a given compound. This review covers the recent advances in new computational methods for relating biological targets based on the similarity of their binding sites. Binding site comparisons are used for the prediction of their most likely ligands, their possible cross reactivity and selectivity. These comparisons can also be used to infer the function of novel uncharacterized proteins.
暂无评论