An automated reasoning framework for translational research

Alberto Riva, Angelo Nuzzo, Mario Stefanelli, Riccardo Bellazzi

Research output: Contribution to journalArticle

Abstract

In this paper we propose a novel approach to the design and implementation of knowledge-based decision support systems for translational research, specifically tailored to the analysis and interpretation of data from high-throughput experiments. Our approach is based on a general epistemological model of the scientific discovery process that provides a well-founded framework for integrating experimental data with preexisting knowledge and with automated inference tools. In order to demonstrate the usefulness and power of the proposed framework, we present its application to Genome-Wide Association Studies, and we use it to reproduce a portion of the initial analysis performed on the well-known WTCCC dataset. Finally, we describe a computational system we are developing, aimed at assisting translational research. The system, based on the proposed model, will be able to automatically plan and perform knowledge discovery steps, to keep track of the inferences performed, and to explain the obtained results.

Original languageEnglish
Pages (from-to)419-427
Number of pages9
JournalJournal of Biomedical Informatics
Volume43
Issue number3
DOIs
Publication statusPublished - Jun 2010

Fingerprint

Translational Medical Research
Genome-Wide Association Study
Decision support systems
Data mining
Genes
Throughput
Experiments
Datasets

Keywords

  • Automated reasoning
  • Genome-Wide Association Studies
  • High-throughput research
  • Knowledge-based systems

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics
  • Medicine(all)

Cite this

An automated reasoning framework for translational research. / Riva, Alberto; Nuzzo, Angelo; Stefanelli, Mario; Bellazzi, Riccardo.

In: Journal of Biomedical Informatics, Vol. 43, No. 3, 06.2010, p. 419-427.

Research output: Contribution to journalArticle

Riva, Alberto ; Nuzzo, Angelo ; Stefanelli, Mario ; Bellazzi, Riccardo. / An automated reasoning framework for translational research. In: Journal of Biomedical Informatics. 2010 ; Vol. 43, No. 3. pp. 419-427.
@article{adcfe4fe15fe461fb9c7620bed39f844,
title = "An automated reasoning framework for translational research",
abstract = "In this paper we propose a novel approach to the design and implementation of knowledge-based decision support systems for translational research, specifically tailored to the analysis and interpretation of data from high-throughput experiments. Our approach is based on a general epistemological model of the scientific discovery process that provides a well-founded framework for integrating experimental data with preexisting knowledge and with automated inference tools. In order to demonstrate the usefulness and power of the proposed framework, we present its application to Genome-Wide Association Studies, and we use it to reproduce a portion of the initial analysis performed on the well-known WTCCC dataset. Finally, we describe a computational system we are developing, aimed at assisting translational research. The system, based on the proposed model, will be able to automatically plan and perform knowledge discovery steps, to keep track of the inferences performed, and to explain the obtained results.",
keywords = "Automated reasoning, Genome-Wide Association Studies, High-throughput research, Knowledge-based systems",
author = "Alberto Riva and Angelo Nuzzo and Mario Stefanelli and Riccardo Bellazzi",
year = "2010",
month = "6",
doi = "10.1016/j.jbi.2009.11.005",
language = "English",
volume = "43",
pages = "419--427",
journal = "Journal of Biomedical Informatics",
issn = "1532-0464",
publisher = "Academic Press Inc.",
number = "3",

}

TY - JOUR

T1 - An automated reasoning framework for translational research

AU - Riva, Alberto

AU - Nuzzo, Angelo

AU - Stefanelli, Mario

AU - Bellazzi, Riccardo

PY - 2010/6

Y1 - 2010/6

N2 - In this paper we propose a novel approach to the design and implementation of knowledge-based decision support systems for translational research, specifically tailored to the analysis and interpretation of data from high-throughput experiments. Our approach is based on a general epistemological model of the scientific discovery process that provides a well-founded framework for integrating experimental data with preexisting knowledge and with automated inference tools. In order to demonstrate the usefulness and power of the proposed framework, we present its application to Genome-Wide Association Studies, and we use it to reproduce a portion of the initial analysis performed on the well-known WTCCC dataset. Finally, we describe a computational system we are developing, aimed at assisting translational research. The system, based on the proposed model, will be able to automatically plan and perform knowledge discovery steps, to keep track of the inferences performed, and to explain the obtained results.

AB - In this paper we propose a novel approach to the design and implementation of knowledge-based decision support systems for translational research, specifically tailored to the analysis and interpretation of data from high-throughput experiments. Our approach is based on a general epistemological model of the scientific discovery process that provides a well-founded framework for integrating experimental data with preexisting knowledge and with automated inference tools. In order to demonstrate the usefulness and power of the proposed framework, we present its application to Genome-Wide Association Studies, and we use it to reproduce a portion of the initial analysis performed on the well-known WTCCC dataset. Finally, we describe a computational system we are developing, aimed at assisting translational research. The system, based on the proposed model, will be able to automatically plan and perform knowledge discovery steps, to keep track of the inferences performed, and to explain the obtained results.

KW - Automated reasoning

KW - Genome-Wide Association Studies

KW - High-throughput research

KW - Knowledge-based systems

UR - http://www.scopus.com/inward/record.url?scp=77952741514&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77952741514&partnerID=8YFLogxK

U2 - 10.1016/j.jbi.2009.11.005

DO - 10.1016/j.jbi.2009.11.005

M3 - Article

C2 - 19931420

AN - SCOPUS:77952741514

VL - 43

SP - 419

EP - 427

JO - Journal of Biomedical Informatics

JF - Journal of Biomedical Informatics

SN - 1532-0464

IS - 3

ER -