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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

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Computer-based genealogy reconstruction in founder populations.

Giuseppe Milani¹, Corrado Masciullo, Cinzia Sala

¹Department of Computer Engineering and Systems Science, University of Pavia, Pavia, Italy. milani.giuseppe@gmail.com

Journal of Biomedical Informatics

|September 3, 2011

Summary

This study introduces a software tool for reconstructing detailed genealogies from diverse historical records. It successfully mapped a 13-generation family tree from 16th-century Italian population data.

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Area of Science:

Computational Biology
Historical Demography
Bioinformatics

Background:

Genealogy reconstruction faces challenges due to fragmented and inconsistent historical data.
Automated tools are needed to process large volumes of diverse archival records efficiently.

Purpose of the Study:

To develop and evaluate a software tool for comprehensive genealogy reconstruction.
To manage data ambiguities and improve accuracy in historical population studies.

Main Methods:

A rule-based record linkage algorithm for matching heterogeneous data sources.
An iterative approach combining automatic reconstruction with human data revision.
Handling of missing, imprecise, or erroneous input data.

Main Results:

Successful reconstruction of a large-scale genealogy from 16th-century records in Val Borbera, Northern Italy.
The resulting pedigree includes 75,994 trios across 13 generations.
Identified a unique large family comprising 58.9% of the reconstructed population.

Conclusions:

The developed software tool effectively reconstructs complex genealogies from historical data.
The iterative human-in-the-loop approach enhances data quality and matching accuracy.
This methodology provides a robust framework for historical population genetics and demographic research.