Search results for "Biological system"
showing 10 items of 319 documents
Prediction of the chemiluminescent behavior of pharmaceuticals and pesticides.
2001
The present paper deals with the first attempt to apply molecular connectivity calculations to predict a chemical property with analytical usefulness: the chemiluminescent behavior of substances when reacted with common oxidants in a liquid phase. Preliminary evidence when searching for new direct CL methods consisted of the examination of analyte reaction with a wide range of oxidants and media. This task, which results in time-consuming and trial-and-error expensive procedures, is necessary due to ensure empirical or theoretical rules for CL prediction are available. On the other hand, in quantitative structure-activity relationship studies, molecular connectivity is a topological method …
Atom, atom-type and total molecular linear indices as a promising approach for bioorganic and medicinal chemistry: theoretical and experimental asses…
2004
Abstract Helminth infections are a medical problem in the world nowadays. In this paper a novel atom-level chemical descriptor has been applied to estimate the anthelmintic activity. Total and local linear indices and linear discriminant analysis were used to obtain a quantitative model that discriminates between anthelmintic and non-anthelmintic drug-like compounds. The discriminant model has an accuracy of 90.11% in the training set, with a high Matthews’ correlation coefficient (MCC = 0.80). To assess the robustness and predictive power of the obtained model, internal (leave-n-out) and external validation process was performed. The QSAR model correctly classified 88.55% of compounds in t…
Comparative study to predict toxic modes of action of phenols from molecular structures.
2013
Quantitative structure-activity relationship models for the prediction of mode of toxic action (MOA) of 221 phenols to the ciliated protozoan Tetrahymena pyriformis using atom-based quadratic indices are reported. The phenols represent a variety of MOAs including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles and soft electrophiles. Linear discriminant analysis (LDA), and four machine learning techniques (ML), namely k-nearest neighbours (k-NN), support vector machine (SVM), classification trees (CTs) and artificial neural networks (ANNs), have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. M…
Modified nonsink equation for permeability estimation in cell monolayers: comparison with standard methods.
2014
Cell culture permeability experiments are valuable tools in drug development and candidate selection, but the monolayer preparation protocols and the calculations procedures can affect the permeability estimation. Hence, standardization and method suitability demonstration are necessary steps for using permeability data for regulatory and in vivo prediction purposes. Much attention is usually paid to experimental procedure validation and less to the mathematical analysis of the results although the standard equations used imply several assumptions that many times do not hold. The aim of this study was to use a simulation strategy to explore the performance of a new proposed modified nonsink…
Modelling and prediction of retention in high-performance liquid chromatography by using neural networks
1995
Multi-layer feed-forward neural networks trained with an error back-propagation algorithm have been used to model retention behaviour of liquid chromatography as a function of the composition of the mobile phases. Conventional hydro-organic and micellar mobile phases were considered. Accurate retention modelling and prediction have been achieved using mobile phases defined by two, three and four parameters. With micellar mobile phases, the parameters involved included the concentrations of surfactant and organic modifier, pH and temperature. It is shown that neural networks provide a competitive tool to model varied inherent nonlinear relationships of retention behaviour with respect to the…
Prediction and Discrimination of Pharmacological Activity by Using Artificial Neural Networks
2003
The design of new medical drugs is a very complex process in which combinatorial chemistry techniques are used. For this reason, it is very useful to have tools to predict and to discriminate the pharmacological activity of a given molecular compound so that the laboratory experiments can be directed to those molecule groups in which there is a high probability of finding new compounds with the desired properties. This work presents an application of Artificial Neural Networks to the problem of discriminating and predicting pharmacological characteristics of a molecular compound from its topological properties. A large amount of different configurations are tested, yielding very good perfor…
Crowdsourced analysis of fungal growth and branching on microfluidic platforms
2021
Fungal hyphal growth and branching are essential traits that allow fungi to spread and proliferate in many environments. This sustained growth is essential for a myriad of applications in health, agriculture, and industry. However, comparisons between different fungi are difficult in the absence of standardized metrics. Here, we used a microfluidic device featuring four different maze patterns to compare the growth velocity and branching frequency of fourteen filamentous fungi. These measurements result from the collective work of several labs in the form of a competition named the “Fungus Olympics.” The competing fungi included five ascomycete species (ten strains total), two basidiomycete…
Sentinel-3/FLEX Biophysical Product Confidence Using Sentinel-2 Land-Cover Spatial Distributions
2021
The estimation of biophysical variables from remote sensing data raises important challenges in terms of the acquisition technology and its limitations. In this way, some vegetation parameters, such as chlorophyll fluorescence, require sensors with a high spectral resolution that constrains the spatial resolution while significantly increasing the subpixel land-cover heterogeneity. Precisely, this spatial variability often makes that rather different canopy structures are aggregated together, which eventually generates important deviations in the corresponding parameter quantification. In the context of the Copernicus program (and other related Earth Explorer missions), this article propose…
Spatial diversity of chlorine residual in a drinking water distribution system: application of an integrated fuzzy logic technique
2014
A reduction in the concentration of chlorine, which is used as a chemical disinfectant for water in drinking water distribution systems, can be considered to be an index of the progressive deterioration of water quality. In this work, attention is given to the spatial distribution of the residual chlorine in drinking water distribution systems. The criterion for grouping the water-quality parameters normally used is highly subjective and often based on data that are not correctly identified. In this paper, a cluster analysis based on fuzzy logic is applied. The advantage of the proposed procedure is that it allows a user to identify (in an automatic way and without any specific assumption) …
Can ultraviolet cues function as aposematic signals?
2001
The fact that birds are sensitive to ultraviolet light (UV, 320–400 nm) has been largely ignored by previous studies of aposematism. Therefore, in the present article we investigated whether great tits preferred ultraviolet-reflecting colors compared to colors without UV reflection and whether UV cues alone could function as aposematic signals. We were able to manipulate prey visibility in UV light by changing the UV reflectance of prey items as well as altering the lighting conditions. In order to perform a preference experiment we used three pairs of colors (green UV vs. green, gray UV vs. gray, yellow UV vs. yellow) on a black background. The birds ate both UV types equally for all three…