Search results for "Discriminant Analysis"
showing 10 items of 229 documents
Neural Network Techniques for Metal Forming Design
1993
Neural networks are computing structures able to predict the behaviour of a system on the basis of the knowledge of facts; main characteristic of a network is the capability to find a rule in a very complex environment. In the paper a neural network, based on the results of FEM simulations, is utilized to predict the occurrence of defects in a forward extrusion metal forming process. In particular a three layers neural network, relating the operative parameters with the failure or the success of the working process, has been used and the back-propagation algorithm has been employed to train the network. Few experimental data were enough to train the neural network allowing to achieve better…
Immunological Diagnosis of Human Cystic Echinococcosis: Utility of Discriminant Analysis Applied to the Enzyme-Linked Immunoelectrotransfer Blot
1999
ABSTRACT An enzyme-linked immunoelectrotransfer blot for the diagnosis of human hydatid disease was performed, and the different antibody responses were analyzed by a discriminant analysis. This multivariate technique gave us, first, a selection of the most important responses against Echinococcus granulosus infection and, second, a procedure for the classification of patients into two groups: patients with hydatid disease and patients without a history of hydatid disease. This method was applied to 67 patients, 25 with active hydatid cysts (24 hepatic and 1 pulmonary) and 42 without a history of hydatid disease and was compared with the results obtained by conventional serology: indirect h…
Authentication of Alicante’s Mountain cherries protected designation of origin by their mineral profile
2011
Abstract Chemometric analysis of inductively coupled plasma optical emission spectroscopy (ICP-OES) data was employed to verify the origin of cherry samples of different areas of Spain: Aragon, Caceres, Castellon, Huesca and Alicante’s Mountain Protected Geographic Indication (PGI). The ability of multivariate analysis methods, such as discriminant analysis (DA), was used to achieve cherry classification from their mineral content. The study was performed using 22 variables (concentrations of Al, As, B, Ba, Be, Bi, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Se, Sr, Ti and Te) and 23 variables (concentrations of Al, As, B, Ba, Be, Bi, Ca, Cd, Cr, Cu, Fe, K, Li, Mg, Mo, Na, Ni, Pb, Se, Sr…
DesMol2, an Effective Tool for the Construction of Molecular Libraries and Its Application to QSAR Using Molecular Topology
2019
A web application, DesMol2, which offers two main functionalities, is presented: the construction of molecular libraries and the calculation of topological indices. These functionalities are explained through a practical example of research of active molecules to the formylpeptide receptor (FPR), a receptor associated with chronic inflammation in systemic amyloidosis and Alzheimer&rsquo
Novel 3D bio-macromolecular bilinear descriptors for protein science: Predicting protein structural classes
2015
In the present study, we introduce novel 3D protein descriptors based on the bilinear algebraic form in the ℝn space on the coulombic matrix. For the calculation of these descriptors, macromolecular vectors belonging to ℝn space, whose components represent certain amino acid side-chain properties, were used as weighting schemes. Generalization approaches for the calculation of inter-amino acidic residue spatial distances based on Minkowski metrics are proposed. The simple- and double-stochastic schemes were defined as approaches to normalize the coulombic matrix. The local-fragment indices for both amino acid-types and amino acid-groups are presented in order to permit characterizing fragme…
3D-Chiral quadratic indices of the ‘molecular pseudograph’s atom adjacency matrix’ and their application to central chirality codification: classific…
2004
Quadratic indices of the 'molecular pseudograph's atom adjacency matrix' have been generalized to codify chemical structure information for chiral drugs. These 3D-chiral quadratic indices make use of a trigonometric 3D-chirality correction factor. These indices are nonsymmetric and reduced to classical (2D) descriptors when symmetry is not codified. By this reason, it is expected that they will be useful to predict symmetry-dependent properties. 3D-Chirality quadratic indices are real numbers and thus, can be easily calculated in TOMOCOMD-CARDD software. These descriptors circumvent the inability of conventional 2D quadratic indices (Molecules 2003, 8, 687-726. http://www.mdpi.org) and othe…
Atom-based Stochastic and non-Stochastic 3D-Chiral Bilinear Indices and their Applications to Central Chirality Codification
2006
Abstract Non-stochastic and stochastic 2D bilinear indices have been generalized to codify chemical structure information for chiral drugs, making use of a trigonometric 3D-chirality correction factor. In order to evaluate the effectiveness of this novel approach in drug design we have modeled the angiotensin-converting enzyme inhibitory activity of perindoprilate's σ-stereoisomers combinatorial library. Two linear discriminant analysis models, using non-stochastic and stochastic linear indices, were obtained. The models had shown an accuracy of 95.65% for the training set and 100% for the external prediction set. Next the prediction of the σ-receptor antagonists of chiral 3-(3-hydroxypheny…
Discrimination and selection of new potential antibacterial compounds using simple topological descriptors.
2003
Abstract The aim of the work was to discriminate between antibacterial and non-antibacterial drugs by topological methods and to select new potential antibacterial agents from among new structures. The method used for antibacterial activity selection was a linear discriminant analysis (LDA). It is possible to obtain a QSAR interpretation of the information contained in the discriminant function. We make use of the pharmacological distribution diagrams (PDDs) as a visualizing technique for the identification and selection of new antibacterial agents.
TOMOCOMD-CARDD descriptors-based virtual screening of tyrosinase inhibitors: evaluation of different classification model combinations using bond-bas…
2006
Abstract A new set of bond-level molecular descriptors (bond-based linear indices) are used here in QSAR (quantitative structure–activity relationship) studies of tyrosinase inhibitors, for finding functions that discriminate between the tyrosinase inhibitor compounds and inactive ones. A database of 246 compounds was collected for this study; all organic chemicals were reported as tyrosinase inhibitors; they had great structural diversity. This dataset can be considered as a helpful tool, not only for theoretical chemists but also for other researchers in this area. The set used as inactive has 412 drugs with other clinical uses. Twelve LDA-based QSAR models were obtained, the first six us…
Non-stochastic quadratic fingerprints and LDA-based QSAR models in hit and lead generation through virtual screening: theoretical and experimental as…
2005
In order to explore the ability of non-stochastic quadratic indices to encode chemical information in antimalarials, four quantitative models for the discrimination of compounds having this property were generated and statistically compared. Accuracies of 90.2% and 83.3% for the training and test sets, respectively, were observed for the best of all the models, which included non-stochastic quadratic fingerprints weighted with Pauling electronegativities. With a comparative purpose and as a second validation experiment, an exercise of virtual screening of 65 already-reported antimalarials was carried out. Finally, 17 new compounds were classified as either active/inactive ones and experimen…