Biomedical subjects

S Merler

Publications and source records attributed to S Merler.

3 recordsLinked to original sources

PubMed1997

Ixodes ricinus (Acari: Ixodidae) infestation on roe deer (Capreolus capreolus) in Trentino, Italian Alps.

The most important tick-deer system potentially supporting the epidemiology of Lyme disease in the Italian Alps is that regarding Ixodes ricinus (L.) and roe deer (Capreolus capreolus L.). In this study, the pattern of tick infestation on 562 male roe deer harvested in September 1994 in 56 game districts of Trentino, Northern Italy, was assessed. The prevalence and density of infestation by I. ricinus were analyzed by a model based on classification and regression trees (CART), using both discrete and continuous variables concerning environmental and host parameters. The model discriminated attitude and host density as the 2 variables having the greatest effect on the prevalence and density of infestation of deer; the levels of infestation were higher at an altitude below 1125 m or at roe deer densities over 8.5 head per 100 ha. The density of tick infestation tended to be higher in older roe deer.

Age Factors↗

PubMed1996

Classification tree methods for analysis of mesoscale distribution of Ixodes ricinus (Acari:Ixodidae) in Trentino, Italian Alps.

Cases of Lyme disease and tick-borne encephalitis were recognized recently in the Province of Trento, Italian Alps. Assessment of areas of potential risk for these tick-borne diseases is carried out by a model based on classification and regression trees (CART), using both discrete and continuous variables. Data on Ixodes ricinus (L.) occurrence resulted from extensive sampling carried out by standard methods in 99 sites over an area of approximately 2,700 km2 in the Province of Trento. A series of environmental parameters were recorded from each site and population densities of roe deer, Capreolus capreolus (L.), were considered. The CART model discriminates 2 variables that appear to have the greatest effect on the mesoscale occurrence of ticks: altitude and geological substratum, with a drastic decrease of tick frequency above an altitude of approximately 1,100 m and on volcanic substrata. The model is effective in identifying the mesoscale areas at greater potential risk, with a relatively low sampling effort.

Animals↗

PubMedDate not supplied

An accelerated procedure for recursive feature ranking on microarray data.

We describe a new wrapper algorithm for fast feature ranking in classification problems. The Entropy-based Recursive Feature Elimination (E-RFE) method eliminates chunks of uninteresting features according to the entropy of the weights distribution of a SVM classifier. With specific regard to DNA microarray datasets, the method is designed to support computationally intensive model selection in classification problems in which the number of features is much larger than the number of samples. We test E-RFE on synthetic and real data sets, comparing it with other SVM-based methods. The speed-up obtained with E-RFE supports predictive modeling on high dimensional microarray data.

Oligonucleotide Array Sequence Analysis↗