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Modelling fingerprint pattern inheritance.

Authors: D, Cocchi; M, Di Bacco;

Modelling fingerprint pattern inheritance.

Abstract

The authors compare some genetic triallelic models for finger-print pattern inheritance built according to the Galton classification. These models keep at the same time into account the available information on fingerprints: population frequencies for individuals, matchings in couples of MZ-twins and in families composed of parents and their offspring. For every finger, on the basis of the data for individuals and twins, the probabilities of the genotypic population frequencies and a penetrance value are evaluated as parameters of a support (likelihood) function for each model. Then, by utilizing the data on families, the support given to the proposed models is evaluated. Finally, the support of the alternative models is synoptically considered for comparative purposes. In the present paper these models are tried with reliable data, collected and classified by Alciati and Folin, of the Institute of Anthropology of the University of Padua. The results substantially agree with the hypotheses formulated by other authors who did not utilize statistical models.

Keywords

Phenotype, Genotype, Models, Genetic, Pregnancy, Statistics as Topic, Humans, Female, Twins, Monozygotic, Dermatoglyphics

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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