The massive amounts of data generated by high-throughput experiments makes modern biomedical research a data-intensive discipline, shifting the research methodology from a hypothesis-based approach to a hypothesis-free one. A formal procedure should be defined to properly design a study, understand the outcomes and plan improvements for each task performed during the experiments. Such formal approach needs the identification of a high-level conceptual model of the knowledge discovery process occurring in genome-wide studies: this is what existing computational tools lack. Starting from an epistemological model of the discovery process proposed for diagnostic reasoning, we describe how the design and execution of modern genome-wide studies can be modelled using the same framework. We show the general validity of the model, how it can be instantiated to model typical scenarios of genome-wide Studies, and how we use it to develop tools aimed at building semi-automated reasoning systems.

An architecture for automated reasoning systems for genome-wide studies

NUZZO, ANGELO;RIVA, ALBERTO;STEFANELLI, MARIO;BELLAZZI, RICCARDO
2009-01-01

Abstract

The massive amounts of data generated by high-throughput experiments makes modern biomedical research a data-intensive discipline, shifting the research methodology from a hypothesis-based approach to a hypothesis-free one. A formal procedure should be defined to properly design a study, understand the outcomes and plan improvements for each task performed during the experiments. Such formal approach needs the identification of a high-level conceptual model of the knowledge discovery process occurring in genome-wide studies: this is what existing computational tools lack. Starting from an epistemological model of the discovery process proposed for diagnostic reasoning, we describe how the design and execution of modern genome-wide studies can be modelled using the same framework. We show the general validity of the model, how it can be instantiated to model typical scenarios of genome-wide Studies, and how we use it to develop tools aimed at building semi-automated reasoning systems.
2009
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Esperti anonimi
Inglese
contributo
12th Conference on Artificial Intelligence in Medicine, AIME 2009
2009
Verona, ita
Internazionale
STAMPA
5651
426
430
5
3642029752
3642029752
Decision support system; Genome-wide studies; Reasoning models; Computer Science (all); Theoretical Computer Science
no
none
Nuzzo, Angelo; Riva, Alberto; Stefanelli, Mario; Bellazzi, Riccardo
273
info:eu-repo/semantics/conferenceObject
4
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1127108
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