Suitability of GRIND-based principal properties for the description of molecular similarity and ligand-based virtual screening

The information provided by the alignment-independent GRid Independent Descriptors (GRIND) can be condensed by the application of principal component analysis, obtaining a small number of principal properties (GRIND-PP), which is more suitable for describing molecular similarity. The objective of the present study is to optimize diverse parameters involved in the obtention of the GRIND-PP and validate their suitability for applications, requiring a biologically relevant description of the molecular similarity. With this aim, GRIND-PP computed with a collection of diverse settings were used to carry out ligand-based virtual screening (LBVS) on standard conditions. The quality of the results obtained was remarkable and comparable with other LBVS methods, and their detailed statistical analysis allowed to identify the method settings more determinant for the quality of the results and their optimum. Remarkably, some of these optimum settings differ significantly from those used in previously published applications, revealing their unexplored potential. Their applicability in large compound database was also explored by comparing the equivalence of the results obtained using either computed or projected principal properties. In general, the results of the study confirm the suitability of the GRIND-PP for practical applications and provide useful hints about how they should be computed for obtaining optimum results.

[Archives de la Parole]. , [Chant de batelier] : [en Tamil (dialecte kasuva)] / [Sir George Grierson], éd. ; Linguistic survey of India ; Bommah, chant principal et une autre voix d'homme

[Traditions. Asie. Inde. Province de Madras [i.e. Chennai]]

Eina de mobilitat pel sistema de la producció d’Ormetal

L’objectiu principal d’aquest projecte consisteix en realitzar l’estudi, l' anàlisi, el disseny, i el desenvolupament d’una aplicació que millori i faciliti la tasca d’un empleat que treballi fora de l’empresa. Es fa una anàlisi dels requeriments de l’aplicació, es fa el model d’anàlisi i tot seguit el model de disseny, i s’implementarà mitjançant les eines que utilitza la nostra empresa o les que millor s’adaptin a ella. S’analitza també el tipus i el volum d’informació que haurà de manejar. Durant el procés de cada una de les etapes de desenvolupament s’aniran realitzant les corresponents proves per, finalment, realitzar una posada en marxa sobre un empleat a mode de proves en un entorn real. Degut a la necessitat de mobilitat dels comercials s’utilitzen dispositius PDA (Personal Digital Assistant) per al desenvolupament de l’aplicació que els permetrà realitzar les seves tasques. En canvi, l’aplicació corporativa de gestió de l’empresa està situada en un servidor Windows, i per centralitzar i gestionar la informació de les PDA s’utilitzarà una aplicació sota el sistema Windows. L’aplicació s’haurà de confeccionar en funció de les dades que es vulgui que el comercial pugui consultar sobre un client, obra, ... Per millorar-ne la seva funcionalitat, es permetrà l’opció de multi-llenguatge. L’aplicació de la PDA tindrà a grans trets les següents funcionalitats: gestió de clients, gestió de contactes, consultar gestions comercials, consultar obres dels clients, consultar el planning i l’estat dels muntadors. Altres processos que haurà de permetre l’aplicació son: la configuració i instal·lació de l’aplicació en els dispositius PDA i la càrrega i el traspàs de les dades entre l’aplicació del PDA i l’aplicació corporativa de l’empresa

Principal curves and principal oriented points

Principal curves have been defined Hastie and Stuetzle (JASA, 1989) assmooth curves passing through the middle of a multidimensional dataset. They are nonlinear generalizations of the first principalcomponent, a characterization of which is the basis for the principalcurves definition.In this paper we propose an alternative approach based on a differentproperty of principal components. Consider a point in the space wherea multivariate normal is defined and, for each hyperplane containingthat point, compute the total variance of the normal distributionconditioned to belong to that hyperplane. Choose now the hyperplaneminimizing this conditional total variance and look for thecorresponding conditional mean. The first principal component of theoriginal distribution passes by this conditional mean and it isorthogonal to that hyperplane. This property is easily generalized todata sets with nonlinear structure. Repeating the search from differentstarting points, many points analogous to conditional means are found.We call them principal oriented points. When a one-dimensional curveruns the set of these special points it is called principal curve oforiented points. Successive principal curves are recursively definedfrom a generalization of the total variance.

O património geomorfológico do Vale da Ribeira Principal: parque natural da serra da Malagueta, ilha de Santiago, Cabo Verdeavaliação e propostas de valorização

Resumo alargado disponível em português e inglês

Report on a special investigation of the Assistant Director of the Camp Adventure program at the University of Northern Iowa for the period January 1, 2006 through March 31, 2008

Report on a special investigation of the Assistant Director of the Camp Adventure program at the University of Northern Iowa for the period January 1, 2006 through March 31, 2008

On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions

Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.