Observatorio de I+D+i UPM

Memorias de investigación
Capítulo de libro:
Bioinformatics linkage of heterogeneous clinical and genomic information in support of personalized medicine
Áreas de investigación
  • Inteligencia artificial
Biomedical Informatics as a whole faces a difficult epistemological task, since there is no foundation to explain the complexities of modeling clinical medicine and the many relationships between genotype, phenotype, and environment. This paper discusses current efforts to investigate such relationships, intended to lead to better diagnostic and therapeutic procedures and the development of treatments that could make personalized medicine a reality. METHODS: To achieve this goal there are a number of issues to overcome. Primary are the rapidly growing numbers of heterogeneous data sources which must be integrated to support personalized medicine. Solutions involving the use of domain driven information models of heterogeneous data sources are described in conjunction with controlled ontologies and terminologies. A number of such applications are discussed. RESULTS: Researchers have realized that many dimensions of biology and medicine aim to understand and model the informational mechanisms that support more precise clinical diagnostic, prognostic and therapeutic procedures. As long as data grows exponentially, novel Biomedical Informatics approaches and tools are needed to manage the data. Although researchers are typically able to manage this information within specific, usually narrow contexts of clinical investigation, novel approaches for both training and clinical usage must be developed. CONCLUSION: After some preliminary overoptimistic expectations, it seems clear now that genetics alone cannot transform medicine. In order to achieve this, heterogeneous clinical and genomic data source must be integrated in scientifically meaningful and productive systems. This will include hypothesis-driven scientific research systems along with well understood information systems to support such research. These in turn will enable the faster advancement of personalized medicine.
Edición del Libro
Editorial del Libro
Yearb Med Inform
13 978-3-7945-2651-2
Título del Libro
IMIA Yearbook
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Esta actividad pertenece a memorias de investigación
  • Participante: LJ Frey
  • Autor: Victor Manuel Maojo Garcia (UPM)
  • Participante: JA Mitchell
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Informática Biomédica (LIA)
  • Departamento: Inteligencia Artificial
S2i 2022 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)