Persona:
Martínez Tomás, Rafael

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0000-0003-4706-7168
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Martínez Tomás
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Rafael
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2009 - 200912020 - 20233
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Autor: Rincón Zamorano, Mariano × Tipo: artículo ×

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Mostrando 1 - 4 de 4
  • Miniatura
    Publicación
    An overview of graph databases and their applications in the biomedical domain
    (Oxford University Press, 2021-05-18) Timón Reina, Santiago; Rincón Zamorano, Mariano; Martínez Tomás, Rafael
    Over the past couple of decades, the explosion of densely interconnected data has stimulated the research, development and adoption of graph database technologies. From early graph models to more recent native graph databases, the landscape of implementations has evolved to cover enterprise-ready requirements. Because of the interconnected nature of its data, the biomedical domain has been one of the early adopters of graph databases, enabling more natural representation models and better data integration workflows, exploration and analysis facilities. In this work, we survey the literature to explore the evolution, performance and how the most recent graph database solutions are applied in the biomedical domain, compiling a great variety of use cases. With this evidence, we conclude that the available graph database management systems are fit to support data-intensive, integrative applications, targeted at both basic research and exploratory tasks closer to the clinic.
  • Miniatura
    Publicación
    Integrative Base Ontology for the Research Analysis of Alzheimer’s Disease-Related Mild Cognitive Impairment
    (Frontiers, 2021-02-04) Gómez-Valades Batanero, Alba; Martínez Tomás, Rafael; Rincón Zamorano, Mariano
    Early detection of mild cognitive impairment (MCI) has become a priority in Alzheimer’s disease (AD) research, as it is a transitional phase between normal aging and dementia. However, information on MCI and AD is scattered across different formats and standards generated by different technologies, making it difficult to work with them manually. Ontologies have emerged as a solution to this problem due to their capacity for homogenization and consensus in the representation and reuse of data. In this context, an ontology that integrates the four main domains of neurodegenerative diseases, diagnostic tests, cognitive functions, and brain areas will be of great use in research. Here, we introduce the first approach to this ontology, the Neurocognitive Integrated Ontology (NIO), which integrates the knowledge regarding neuropsychological tests (NT), AD, cognitive functions, and brain areas. This ontology enables interoperability and facilitates access to data by integrating dispersed knowledge across different disciplines, rendering it useful for other research groups. To ensure the stability and reusability of NIO, the ontology was developed following the ontology-building life cycle, integrating and expanding terms from four different reference ontologies. The usefulness of this ontology was validated through use-case scenarios.
  • Miniatura
    Publicación
    A Knowledge Graph Framework for Dementia Research Data
    (MDPI, 2023-09-20) Timón Reina, Santiago; Kirsebom, Bjørn-Eivind; Fladby, Tormod; Rincón Zamorano, Mariano; Martínez Tomás, Rafael
    Dementia disease research encompasses diverse data modalities, including advanced imaging, deep phenotyping, and multi-omics analysis. However, integrating these disparate data sources has historically posed a significant challenge, obstructing the unification and comprehensive analysis of collected information. In recent years, knowledge graphs have emerged as a powerful tool to address such integration issues by enabling the consolidation of heterogeneous data sources into a structured, interconnected network of knowledge. In this context, we introduce DemKG, an open-source framework designed to facilitate the construction of a knowledge graph integrating dementia research data, comprising three core components: a KG-builder that integrates diverse domain ontologies and data annotations, an extensions ontology providing necessary terms tailored for dementia research, and a versatile transformation module for incorporating study data. In contrast with other current solutions, our framework provides a stable foundation by leveraging established ontologies and community standards and simplifies study data integration while delivering solid ontology design patterns, broadening its usability. Furthermore, the modular approach of its components enhances flexibility and scalability. We showcase how DemKG might aid and improve multi-modal data investigations through a series of proof-of-concept scenarios focused on relevant Alzheimer’s disease biomarkers.
  • Miniatura
    Publicación
    On the effect of feedback in multilevel representation spaces for visual surveillance tasks
    (Elsevier, 2009-01) Carmona, Enrique J.; Martínez Campos, Javier; Mira Mira, José; Rincón Zamorano, Mariano; Bachiller Mayoral, Margarita; Martínez Tomás, Rafael
    In this work we propose a general top–down feedback scheme between adjacent description levels to interpret video sequences. This scheme distinguishes two types of feedback: repair-oriented feedback and focus-oriented feedback. With the first it is possible to improve the system's performance and produce more reliable and consistent information, and with the second it is possible to adjust the computational load to match the aims. Finally, the general feedback scheme is used in different examples for a visual surveillance application which improved the final result of each description level by using the information in the higher adjacent level.