Search results for "linear discriminant analysis"
showing 10 items of 163 documents
A rapid method for the differentiation of yeast cells grown under carbon and nitrogen-limited conditions by means of partial least squares discrimina…
2012
This paper shows the ease of application and usefulness of mid-IR measurements for the investigation of orthogonal cell states on the example of the analysis of Pichia pastoris cells. A rapid method for the discrimination of entire yeast cells grown under carbon and nitrogen-limited conditions based on the direct acquisition of mid-IR spectra and partial least squares discriminant analysis (PLS-DA) is described. The obtained PLS-DA model was extensively validated employing two different validation strategies: (i) statistical validation employing a method based on permutation testing and (ii) external validation splitting the available data into two independent sub-sets. The Variable Importa…
Classification of Pecorino cheeses produced in Italy according to their ripening time and manufacturing technique using Fourier transform infrared sp…
2010
Fourier-transform infrared spectroscopy, followed by linear discriminant analysis of the spectral data, was used to classify Italian Pecorino cheeses according to their ripening time and manufacturing technique. The Fourier transform infrared spectra of the cheeses were divided into 18 regions and the normalized absorbance peak areas within these regions were used as predictors. Linear discriminant analysis models were constructed to classify Pecorino cheeses according to different ripening stages (hard and semi-hard) or according to their manufacturing technique (fossa and nonfossa cheeses). An excellent resolution was achieved according to both ripening time and manufacturing technique. A…
Multi-class pairwise linear dimensionality reduction using heteroscedastic schemes
2010
Accepted version of an article published in the journal: Pattern Recognition. Published version on Sciverse: http://dx.doi.org/10.1016/j.patcog.2010.01.018 Linear dimensionality reduction (LDR) techniques have been increasingly important in pattern recognition (PR) due to the fact that they permit a relatively simple mapping of the problem onto a lower-dimensional subspace, leading to simple and computationally efficient classification strategies. Although the field has been well developed for the two-class problem, the corresponding issues encountered when dealing with multiple classes are far from trivial. In this paper, we argue that, as opposed to the traditional LDR multi-class schemes…
Evaluation of the effect of chance correlations on variable selection using Partial Least Squares -Discriminant Analysis
2013
Variable subset selection is often mandatory in high throughput metabolomics and proteomics. However, depending on the variable to sample ratio there is a significant susceptibility of variable selection towards chance correlations. The evaluation of the predictive capabilities of PLSDA models estimated by cross-validation after feature selection provides overly optimistic results if the selection is performed on the entire set and no external validation set is available. In this work, a simulation of the statistical null hypothesis is proposed to test whether the discrimination capability of a PLSDA model after variable selection estimated by cross-validation is statistically higher than t…
A New Technique for Vibration-Based Diagnostics of Fatigued Structures Based on Damage Pattern Recognition via Minimization of Misclassification Prob…
2017
Vibration-based diagnostics provide various methods to detect, locate, and characterize damage in structural and mechanical systems by examining changes in measured vibration response. Research in vibration-based damage recognition has been rapidly expanding over the last few years. The basic idea behind this technology is that modal parameters (notably frequencies, mode shapes, and modal damping) are functions of the physical properties of the structure (mass, damping, and stiffness). Therefore, changes in the physical properties will cause detectable changes in the modal properties. In investigations, many techniques were applied to recognize damage in structural and mechanical systems, b…
Topological virtual screening: a way to find new anticonvulsant drugs from chemical diversity.
2003
A topological virtual screening (tvs) test is presented, which is capable of identifying new drug leaders with anticonvulsant activity. Molecular structures of both anticonvulsant-active and non active compounds, extracted from the Merck Index database, were represented using topological indexes. By means of the application of a linear discriminant analysis to both sets of structures, a topological anticonvulsant model (tam) was obtained, which defines a connectivity function. On the basis of this model, 41 new structures with anticonvulsant activity have been identified by a topological virtual screening.
Application of molecular topology to the prediction of inhibition of Trypanosoma cruzi Hexokinase by bisphosphonates
2008
Se ha desarrollado un modelo topológico-matemático para la búsqueda de nuevos derivados bisfosfonatos activos frente a la hexokinasa de Trypanosoma cruzi. Utilizando el análisis lineal discriminante se ha seleccionado una función con cuatro variables capaz de predecir adecuadamente la CI50 para cada compuesto de las series de entrenamiento y test. El modelo propuesto se ha aplicado a una librería molecular y se han propuesto nuevas estructuras potencialmente activas frente a T. cruzi.
Applying pattern recognition methods plus quantum and physico-chemical molecular descriptors to analyze the anabolic activity of structurally diverse…
2008
The great cost associated with the development of new anabolic-androgenic steroid (AASs) makes necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, quantum, and physicochemical molecular descriptors, plus linear discriminant analysis (LDA) were used to analyze the anabolic/androgenic activity of structurally diverse steroids and to discover novel AASs, as well as also to give a structural interpretation of their anabolic-androgenic ratio (AAR). The obtained models are able to correctly classify 91.67% (86.27%) of the AASs in the training (test) sets, respectively. The results of predictions on the 10% full-out cross-validation test al…
Computational discovery of novel trypanosomicidal drug-like chemicals by using bond-based non-stochastic and stochastic quadratic maps and linear dis…
2009
Herein we present results of a quantitative structure-activity relationship (QSAR) studies to classify and design, in a rational way, new antitrypanosomal compounds by using non-stochastic and stochastic bond-based quadratic indices. A data set of 440 organic chemicals, 143 with antitrypanosomal activity and 297 having other clinical uses, is used to develop QSAR models based on linear discriminant analysis (LDA). Non-stochastic model correctly classifies more than 93% and 95% of chemicals in both training and external prediction groups, respectively. On the other hand, the stochastic model shows an accuracy of about the 87% for both series. As an experiment of virtual lead generation, the …
Modeling anti-allergic natural compounds by molecular topology.
2013
Molecular topology has been applied to the search of QSAR models able to identify the anti-allergic activity of a wide group of heterogeneous compounds. Through the linear discriminant analysis and artificial neural networks, correct classification percentages above 85% for both the training set and the test set have been obtained. After carrying out a virtual screening with a natural product library, about thirty compounds with theoretical anti-allergic activity have been selected. Among them, hesperidin, naringin, salinomycin, sorbitol, curcumol, myricitrin, diosmin and kinetin stand out. Some of these compounds have already been referenced as having anti-allergic activity.