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Journal ArticleDOI

TOMOCOMD-CARDD descriptors-based virtual screening of tyrosinase inhibitors: evaluation of different classification model combinations using bond-based linear indices.

TLDR
The fitted discriminant functions were used in the selection/identification of new ethylsteroids isolated from herbal plants, looking for tyrosinase inhibitory activity, and provided useful clues that can be used to speed up in the identification of new tyosinase inhibitor compounds.
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This article is published in Bioorganic & Medicinal Chemistry.The article was published on 2007-02-01. It has received 77 citations till now. The article focuses on the topics: Quantitative structure–activity relationship & Molecular descriptor.

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Unified QSAR approach to antimicrobials. Part 3: first multi-tasking QSAR model for input-coded prediction, structural back-projection, and complex networks clustering of antiprotozoal compounds.

TL;DR: The development of an mt-QSAR for more than 500 drugs tested in the literature against different parasites and the outputs of the QSAR are used to construct, by the first time, a multi-species Complex Networks of antiparasite drugs.
Journal ArticleDOI

Supercritical CO2 extract of Cinnamomum zeylanicum: chemical characterization and antityrosinase activity.

TL;DR: The volatile oil of the bark of Cinnamomum zeylanicum was extracted by means of supercritical CO2 fluid extraction in different conditions of pressure and temperature and E-Cinnamaldehyde and eugenol were found to be mainly responsible of this inhibition effect.
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Unified QSAR approach to antimicrobials. 4. Multi-target QSAR modeling and comparative multi-distance study of the giant components of antiviral drug-drug complex networks.

TL;DR: This work uses Linear Discriminant Analysis (LDA) to fit a mt-QSAR model that classify 600 drugs as active or non-active against the 41 different tested species of virus and develops a virtual screening recognizing the model as active 92.7% of compounds.
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General Theory for Multiple Input-Output Perturbations in Complex Molecular Systems. 1. Linear QSPR Electronegativity Models in Physical, Organic, and Medicinal Chemistry

TL;DR: This work reviews general aspects and applications of both perturbation theory and QSPR models and formulates a general-purpose perturbations theory for multiple-boundary Q SPR problems and develops three new QSPr-Perturbation Theory models.
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HP-Lattice QSAR for dynein proteins: Experimental proteomics (2D-electrophoresis, mass spectrometry) and theoretic study of a Leishmania infantum sequence

TL;DR: The first QSAR for dynein proteins is reported here, and a combined experimental and theoretic study of a new dyneIn sequence is reported in order to illustrate the utility of the model to search for potential drug targets with a practical example and the potential use of theQSAR model as a complement to alignment tools.
References
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Book

Applied Multivariate Statistical Analysis

TL;DR: In this article, the authors present an overview of the basic concepts of multivariate analysis, including matrix algebra and random vectors, as well as a strategy for analyzing multivariate models.
Journal ArticleDOI

Applied Multivariate Statistical Analysis.

TL;DR: In this article, the authors present an overview of the basic concepts of multivariate analysis, including matrix algebra and random vectors, as well as a strategy for analyzing multivariate models.
Book

Handbook of Molecular Descriptors

TL;DR: This Users guide notations acronyms list of molecular descriptors contains abbreviations for molecular descriptor values that are useful for counting and topological descriptors calculation.
Journal ArticleDOI

Beware of q2

TL;DR: It is argued that the high value of LOO q2 appears to be the necessary but not the sufficient condition for the model to have a high predictive power, which is the general property of QSAR models developed using LOO cross-validation.
Journal ArticleDOI

Assessing the accuracy of prediction algorithms for classification: an overview

TL;DR: A unified overview of methods that currently are widely used to assess the accuracy of prediction algorithms, from raw percentages, quadratic error measures and other distances, and correlation coefficients, and to information theoretic measures such as relative entropy and mutual information are provided.
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