PuSH - Publication Server of Helmholtz Zentrum München: Application of the PyHasse program features: Sensitivity, similarity, and separability for environmental health data.

Information

Clues to quality of journals

Open Access Policy of Helmholtz Association 2016

CC Licencences

Publication Metrics

Navigation

Home

Deutsch

EVA: Electronic Publishing

New EVA Application

Research

Advanced Search

Browse by ...

... HMGU-Authors/Consortia

... Organizational Structure

... Journal

... Publication Type

... Research Data

... Arbeitsgruppen

... Publication Year

Publication overview

Statistics

Statistics (last 5 years)

OA Publications

Publish

Submit Publication

Import publication from...

...EVA

Report missing publication

Highlights

Support & Contact

Contact persons

Help

Data protection

Helmholtz Open Science

JANE Journal Estimator

SHERPA/RoMEO

DOAJ

Export:

Text

Endnote (RIS) BIB

BibTeX

Voigt, K. ; Scherb, H. ; Brüggemann, R.* ; Schramm, K.-W.

Application of the PyHasse program features: Sensitivity, similarity, and separability for environmental health data.

Stat. Appl. Special Issue, 155-168 (2011)

Publ. Version/Full Text

To article

DOI

	Open Access Gold

Abstract
Metrics
Extra information

It has been evident for decades that many environmental chemicals pose an enormous risk to the environment as well as to humans. There is increasing pressure to intensify the research and to more efficiently evaluate the data on persistent and bioaccumulative chemicals in the environment as well as in human bodies. An appropriate data analysis method is based on the theory of partially ordered sets. The program PyHasse, developed by the third author, provides several features which are useful for gaining information out of the data and drawing conclusions concerning the impact of those chemicals and their prevention. In our data analysis approach we investigated data sets of breast milk samples of women in Denmark and Finland which contained measurable levels of 32 persistent organic pollutants (POPs). Three important features of the PyHasse program are used: The Sensitivity Analysis, the Similarity Analysis and the Separability Analysis. The aim of this discrete mathematical approach is to find differences in the chemicals’ contamination between the healthy boys and those boys who were suffering from congenital malformations (cryptorchidism).

Impact Factor

Scopus SNIP

Altmetric

0.000