A dynamic query system for supporting phenotype mining in genetic studies

Angelo Nuzzo, Daniele Segagni, Giuseppe Milani, Carla Rognoni, Riccardo Bellazzi

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

Abstract

This paper describes an information technology infrastructure aimed at supporting translational bioinformatics studies that require joint management of phenotypic and genotypic data. In particular, we integrated an electronic medical record with an open-source environment for data mining to create a flexible and easy to use query system aimed at supporting the discovery of the most frequent complex traits. We propose a logical formalization to define the phenotypes of interest; this is translated into a graphical interface that allows the user to combine different conditions relative to the electronic medical record data (e.g., the presence of a particular pathology). The phenotypes are then stored in a multidimensional database. Then, the data mining system engine reads the filtered data from the database and executes dynamic queries for analyzing phenotypic data, presenting the results in a multidimensional format through a simple web interface. The system has been applied in a study on genetically isolated individuals, the Val Borbera project.

Original languageEnglish
Title of host publicationStudies in Health Technology and Informatics
Pages1275-1279
Number of pages5
Volume129
Publication statusPublished - 2007
Event12th World Congress on Medical Informatics, MEDINFO 2007 - Brisbane, QLD, Australia
Duration: Aug 20 2007Aug 24 2007

Other

Other12th World Congress on Medical Informatics, MEDINFO 2007
CountryAustralia
CityBrisbane, QLD
Period8/20/078/24/07

Keywords

  • clinical data warehouse
  • complex traits
  • intelligent query
  • phenotype mining

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Fingerprint Dive into the research topics of 'A dynamic query system for supporting phenotype mining in genetic studies'. Together they form a unique fingerprint.

Cite this