Literature DB >> 1820283

Mathematical models for exploring different aspects of genotoxicity and carcinogenicity databases.

R Benigni1, A Giuliani.   

Abstract

One great obstacle to understanding and using the information contained in the genotoxicity and carcinogenicity databases is the very size of such databases. Their vastness makes them difficult to read; this leads to inadequate exploitation of the information, which becomes costly in terms of time, labor, and money. In its search for adequate approaches to the problem, the scientific community has, curiously, almost entirely neglected an existent series of very powerful methods of data analysis: the multivariate data analysis techniques. These methods were specifically designed for exploring large data sets. This paper presents the multivariate techniques and reports a number of applications to genotoxicity problems. These studies show how biology and mathematical modeling can be combined and how successful this combination is.

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Year:  1991        PMID: 1820283      PMCID: PMC1568235          DOI: 10.1289/ehp.919681

Source DB:  PubMed          Journal:  Environ Health Perspect        ISSN: 0091-6765            Impact factor:   9.031


  6 in total

1.  Analysis of the National Toxicology Program data on in vitro genetic toxicity tests using multivariate statistical methods.

Authors:  R Benigni
Journal:  Mutagenesis       Date:  1989-11       Impact factor: 3.000

2.  Statistical exploration of four major genotoxicity data bases: an overview.

Authors:  R Benigni; A Giuliani
Journal:  Environ Mol Mutagen       Date:  1988       Impact factor: 3.216

3.  Prediction of chemical carcinogenicity in rodents from in vitro genetic toxicity assays.

Authors:  R W Tennant; B H Margolin; M D Shelby; E Zeiger; J K Haseman; J Spalding; W Caspary; M Resnick; S Stasiewicz; B Anderson
Journal:  Science       Date:  1987-05-22       Impact factor: 47.728

Review 4.  Predicting carcinogenicity with short-term tests: biological models and operational approaches.

Authors:  R Benigni; A Giuliani
Journal:  Mutat Res       Date:  1988 May-Aug       Impact factor: 2.433

5.  Assembly and preliminary analysis of a genotoxicity data base for predicting carcinogens.

Authors:  M Palajda; H S Rosenkranz
Journal:  Mutat Res       Date:  1985-05       Impact factor: 2.433

6.  The prospects for a simplified and internationally harmonized approach to the detection of possible human carcinogens and mutagens.

Authors:  J Ashby
Journal:  Mutagenesis       Date:  1986-01       Impact factor: 3.000

  6 in total

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