New insights on river water chemistry by using non-centred simplicial principal component analysis: a case study

The use of perturbation and power transformation operations permits the investigation of linear processes in the simplex as in a vectorial space. When the investigated geochemical processes can be constrained by the use of well-known starting point, the eigenvectors of the covariance matrix of a non-centred principal component analysis allow to model compositional changes compared with a reference point. The results obtained for the chemistry of water collected in River Arno (central-northern Italy) have open new perspectives for considering relative changes of the analysed variables and to hypothesise the relative effect of different acting physical-chemical processes, thus posing the basis for a quantitative modelling

On the use of principal components in contemporany population genetics: a case study

In human Population Genetics, routine applications of principal component techniques are often required. Population biologists make widespread use of certain discrete classifications of human samples into haplotypes, the monophyletic units of phylogenetic trees constructed from several single nucleotide bimorphisms hierarchically ordered. Compositional frequencies of the haplotypes are recorded within the different samples. Principal component techniques are then required as a dimension-reducing strategy to bring the dimension of the problem to a manageable level, say two, to allow for graphical analysis. Population biologists at large are not aware of the special features of compositional data and normally make use of the crude covariance of compositional relative frequencies to construct principal components. In this short note we present our experience with using traditional linear principal components or compositional principal components based on logratios, with reference to a specific dataset

Diagnosing Patients Combining Principal Components Analysis and Case Based Reasoning

This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is that the standard PCA techniques are designed to deal with numerical attributes, but our medical data set contains many categorical data and alternative methods as RS-PCA are required. Thus, we propose to hybridize RS-PCA (Regular Simplex PCA) and a simple CBR. Results show how the hybrid system produces similar results when diagnosing a medical data set, that the ones obtained when using the original attributes. These results are quite promising since they allow to diagnose with less computation effort and memory storage

Paper del nucli hidrofòbic principal de la RNasa A en el plegament i desplegament induïts per pressió i temperatura

Utilitzant temperatura i pressió com a agents desnaturalitzants s'ha explorat la contribució a l'estabilitat de diferents residus del principal nucli hidrofòbic de la RNasa A. Aquests resutats suggereixen que el principal nucli hidrofòbic d'aquest enzim, està fortament empaquetat i ha revelat l'existència de reordenacions en l'interior de la proteïna. El mètode dels valors , han permès estudiar el paper de les interaccions hidrofòbiques establertes pels residus del principal nucli hidrofòbic de la RNasa A en el seu estat de transició induït per pressió. En conjunt, aquests resultats suggereixen que l'estat de transició de la RNasa A, s'assemblaria a un glòbul col·lapsat amb una cadena estructurada però amb un debilitat nucli hidrofòbic. S'ha explorat també, el paisatge energètic del plegament/desplegament proteic de la variant Y115W de la RNasa A. L'estat de transició sembla interaccionar fortament amb la capa d'hidratació d'aquest estat, tal i com indiquen els resultats en presència de glicerol.