An integrated IT system for phenotypic and genotypic data mining and management

Angelo Nuzzo, Daniele Segagni, Giuseppe Milani, Cinzia Sala, Cristiana Larizza

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper describes the application of an information technology infrastructure aimed at supporting translational bioinformatics studies which need the joint management of phenotypic and genotypic data. The system provides an integrated and easy to use software environment, based on data warehouse and data mining tools, to discover the most frequent complex phenotypes and search their penetrance and heritability by mapping them on the population pedigree. We first use a logical formalization to define phenotypes of interest in order to retrieve individuals having that phenotype from the electronic medical record. We then use an open-source Web-based data warehouse application for analyzing phenotypic data and presenting the results in a multidimensional format. Relationships between the selected individuals are automatically visualized by integrating in the system an ad-hoc developed pedigree visualization tool. Finally, the application of the system to support a genetic study of an isolated population, the Val Borbera project, is presented.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages180-184
Number of pages5
Volume4594 LNAI
Publication statusPublished - 2007
Event11th Conference on Artificial Intelligence in Medicine, AIME 2007 - Amsterdam, Netherlands
Duration: Jul 7 2007Jul 11 2007

Other

Other11th Conference on Artificial Intelligence in Medicine, AIME 2007
CountryNetherlands
CityAmsterdam
Period7/7/077/11/07

Fingerprint

Data Mining
Integrated System
Data Management
Phenotype
Information management
Data mining
Pedigree
Data warehouses
Data Warehouse
Heritability
Electronic medical equipment
Penetrance
Electronic Health Records
Bioinformatics
Computational Biology
Information Technology
Formalization
Open Source
Web-based
Population

Keywords

  • Clinical data warehouse
  • Data mining
  • Genotype-phenotype association
  • Web-based systems

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Nuzzo, A., Segagni, D., Milani, G., Sala, C., & Larizza, C. (2007). An integrated IT system for phenotypic and genotypic data mining and management. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4594 LNAI, pp. 180-184)

An integrated IT system for phenotypic and genotypic data mining and management. / Nuzzo, Angelo; Segagni, Daniele; Milani, Giuseppe; Sala, Cinzia; Larizza, Cristiana.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4594 LNAI 2007. p. 180-184.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nuzzo, A, Segagni, D, Milani, G, Sala, C & Larizza, C 2007, An integrated IT system for phenotypic and genotypic data mining and management. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4594 LNAI, pp. 180-184, 11th Conference on Artificial Intelligence in Medicine, AIME 2007, Amsterdam, Netherlands, 7/7/07.
Nuzzo A, Segagni D, Milani G, Sala C, Larizza C. An integrated IT system for phenotypic and genotypic data mining and management. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4594 LNAI. 2007. p. 180-184
Nuzzo, Angelo ; Segagni, Daniele ; Milani, Giuseppe ; Sala, Cinzia ; Larizza, Cristiana. / An integrated IT system for phenotypic and genotypic data mining and management. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4594 LNAI 2007. pp. 180-184
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