Ontology-based, Tissue MicroArray oriented, image centered tissue bank

doi:10.1186/1471-2105-9-S4-S4

BMC Bioinformatics

Volume 9
Suppl 4

Viewing options:

Abstract
Full text
PDF (602KB)

Associated material:

PubMed record

Related literature:

Articles citing this article
on BioMed Central
on Google Scholar
on ISI Web of Science
on PubMed Central
Other articles by authors
on Google Scholar

Viti F
Merelli I
Caprera A
Lazzari B
Stella A
Milanesi L

on PubMed

Viti F
Merelli I
Caprera A
Lazzari B
Stella A
Milanesi L
Related articles/pages
on Google

on Google Scholar

on PubMed

Tools:

Post to:

This article is part of the supplement: A Semantic Web for Bioinformatics: Goals, Tools, Systems, Applications .

Research

Ontology-based, Tissue MicroArray oriented, image centered tissue bank

Federica Viti¹^,3 , Ivan Merelli¹ , Andrea Caprera² , Barbara Lazzari² , Alessandra Stella² and Luciano Milanesi¹

¹Istituto di Tecnologie Biomediche – Consiglio Nazionale delle Ricerche, Segrate (Milan) 20090, Italy

²Parco Tecnologico Padano, Cascina Codazza (Lodi) 26900, Italy

³Biolab - Department of Computer Science, Control Systems and Telecommunications (DIST) - University of Genoa, Genoa 16100, Italy

author email corresponding author email

BMC Bioinformatics 2008, 9(Suppl 4):S4doi:10.1186/1471-2105-9-S4-S4


Published:	25 April 2008

Abstract

Background

Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information.

Results

In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data.

Conclusions

Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes.