Ara es mostren els items 78-97 de 129

    • Kernel generative topographic mapping of protein sequences 

      Cárdenas, Martha Ivón; Vellido Alcacena, Alfredo; Olier Caparroso, Iván; Rovira, Xavier; Giraldo, Jesús (IGI Global, 2012-06)
      Capítol de llibre
      Accés restringit per política de l'editorial
    • Label noise in subtype discrimination of class C G protein-coupled receptors: A systematic approach to the analysis of classification errors 

      Koenig, Caroline; Cárdenas Domíınguez, Martha Ivón; Giraldo Arjonilla, Jesús; Alquézar Mancho, René; Vellido Alcacena, Alfredo (2015-09-29)
      Article
      Accés obert
      Background: The characterization of proteins in families and subfamilies, at different levels, entails the definition and use of class labels. When the adscription of a protein to a family is uncertain, or even wrong, this ...
    • Layer-wise relevance analysis for motif recognition in the activation pathway of the ß2-adrenergic GPCR receptor 

      Gutiérrez Mondragón, Mario Alberto; König, Caroline; Vellido Alcacena, Alfredo (2023-01-06)
      Article
      Accés obert
      G-protein-coupled receptors (GPCRs) are cell membrane proteins of relevance as therapeutic targets, and are associated to the development of treatments for illnesses such as diabetes, Alzheimer’s, or even cancer. Therefore, ...
    • Leveraging data science for a personalized haemodialysis 

      Hueso, Miguel; Haro Martín, Luis de; Calabria, Jordi; Dal-Re, R; Tebe, C; Gibert, Karina; Cruzado, Josep M; Vellido Alcacena, Alfredo (Karger, 2020-11)
      Article
      Accés obert
      The 2019 Science for Dialysis Meeting at Bellvitge University Hospital was devoted to the challenges and opportunities posed by the use of data science to facilitate precision and personalized medicine in nephrology, and ...
    • Long short-term memory to predict 3D amino acids positions in GPCR molecular dynamics 

      López Correa, Juan Manuel; König, Caroline; Vellido Alcacena, Alfredo (IOS Press, 2022)
      Text en actes de congrés
      Accés obert
      G-Protein Coupled Receptors (GPCRs) are a big family of eukaryotic cell transmembrane proteins, responsible for numerous biological processes. From a practical viewpoint around 34% of the drugs approved by the US Food and ...
    • Machine learning in critical care: state-of-the-art and a sepsis case study 

      Vellido Alcacena, Alfredo; Ribas Ripoll, Vicent; Morales, Carlos; Ruiz Sanmartín, Adolf; Ruiz Rodriguez, Juan Carlos (2018-11-20)
      Article
      Accés obert
      Background: Like other scientific fields, such as cosmology, high-energy physics, or even the life sciences, medicine and healthcare face the challenge of an extremely quick transformation into data-driven sciences. This ...
    • Machine learning in human cancer research 

      Vellido Alcacena, Alfredo; Lisboa, Paulo J.G. (Nova Science Publishers, 2007)
      Capítol de llibre
      Accés restringit per política de l'editorial
      Evidence-based medicine has grown in stature over three decades and is now regarded a key development of modern medicine. The evidence base can be heterogeneous, involving both qualitative knowledge and measured quantitative ...
    • Making machine learning models interpretable 

      Vellido Alcacena, Alfredo; Martin Guerrero, Jose D.; Lisboa, Paulo J.G. (2012)
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    • Making nonlinear manifold learning models interpretable: the manifold grand tour 

      Lisboa, Paulo J.G.; Martin, Jose D.; Vellido Alcacena, Alfredo (2015-12)
      Article
      Accés obert
      Dimensionality reduction is required to produce visualisations of high dimensional data. In this framework, one of the most straightforward approaches to visualising high dimensional data is based on reducing complexity ...
    • Manifold learning visualization of metabotropic glutamate receptors 

      Cárdenas Domínguez, Martha Ivón; Vellido Alcacena, Alfredo; Giraldo Arjonilla, Jesús (IOS Press, 2014)
      Text en actes de congrés
      Accés obert
      G-Protein-Coupled Receptors (GPCRs) are cell membrane proteins with a key role in biological processes. GPCRs of class C, in particular, are of great interest in pharmacology. The lack of knowledge about their 3-D structures ...
    • Metrics for probabilistic geometries 

      Tosi, Alessandra; Hauberg, Søren; Vellido Alcacena, Alfredo; Lawrence, Neil D. (AUAI Press (Association for Uncertainty in Artificial Intelligence), 2014)
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      We investigate the geometrical structure of probabilistic generative dimensionality reduction models using the tools of Riemannian geometry. We explicitly define a distribution over the natural metric given by the models. ...
    • Misclassification of class C G-protein-coupled receptors as a label noise problem 

      König, Caroline; Vellido Alcacena, Alfredo; Alquézar Mancho, René; Giraldo Arjonilla, Jesús (2014)
      Comunicació de congrés
      Accés obert
      G-Protein-Coupled Receptors (GPCRs) are cell membrane proteins of relevance to biology and pharmacology. Their supervised classification in subtypes is hampered by label noise, which stems from a combination of expert ...
    • Missing data imputation through generative topographic mapping as a mixture of t-distributions: Theoretical developments 

      Vellido Alcacena, Alfredo (2004-11)
      Report de recerca
      Accés obert
      The Generative Topographic Mapping (GTM) was originally conceived as a probabilistic alternative to the well-known, neural network-inspired, Self-Organizing Map (SOM). The GTM can also be interpreted as a constrained mixture ...
    • Molecular dynamics forecasting of transmembrane regions in GPRCs by recurrent neural networks 

      López Correa, Juan Manuel; König, Caroline; Vellido Alcacena, Alfredo (Institute of Electrical and Electronics Engineers (IEEE), 2022)
      Text en actes de congrés
      Accés obert
      G protein-coupled receptors are a large super-family of cell membrane proteins that play an important physiological role as transmitters of extra-cellular signals. Signal transmission through the cell membrane depends on ...
    • Network community cluster-based analysis for the identification of potential leukemia drug targets 

      Rodríguez Bazaga, Adrián; Vellido Alcacena, Alfredo (Springer, 2019)
      Comunicació de congrés
      Accés obert
      Leukemia is a hematologic cancer which develops in blood tissue and causes rapid generation of immature and abnormal-shaped white blood cells. It is one of the most prominent causes of death in both men and women for which ...
    • NMF for quality control of multi-modal retinal images for diagnosis of diabetes mellitus and diabetic retinopathy 

      Benali Bendahmane, Anass; Carrera Escale, Laura; Christin, Ann; Martín Pinardel, Ruben; Alé Chilet, Anibal; Barraso Rodrigo, Marina; Bernal Morales, Carolina; Marín Martinez, Sara; Romero Merino, Enrique; Vellido Alcacena, Alfredo (Springer, 2022)
      Text en actes de congrés
      Accés obert
      In current ophthalmology, images of the vascular system in the human retina are used as exploratory proxies for pathologies affecting different organs. In this brief paper, we use multi-modal retinal images for assisting ...
    • On the benefits for model regularization of a variational formulation of GTM 

      Olier Caparroso, Iván; Vellido Alcacena, Alfredo (IEEE, 2008)
      Text en actes de congrés
      Accés obert
      Generative Topographic Mapping (GTM) is a manifold learning model for the simultaneous visualization and clustering of multivariate data. It was originally formulated as a constrained mixture of distributions, for which ...
    • On the computation of the geodesic distance with an application to dimensionality reduction in a neuro-oncology problem 

      Cruz Barbosa, Raúl; Bautista Villavicencio, David; Vellido Alcacena, Alfredo (Springer, 2011)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      Manifold learning models attempt to parsimoniously describe multivariate data through a low-dimensional manifold embedded in data space. Similarities between points along this manifold are often expressed as Euclidean ...
    • On the improvement of the mapping trustworthiness and continuity of a manifold learning model 

      Cruz Barbosa, Raúl; Vellido Alcacena, Alfredo (2008-11)
      Article
      Accés restringit per política de l'editorial
      Manifold learningmethodsmodel high-dimensional data through low-dimensional manifolds embedded in the observed data space. This simplification implies that their are prone to trustworthiness and continuity errors. Generative ...
    • On the use of graphical models to study ICU outcome prediction in septic patients treated with statins 

      Ribas, Vicent J.; Caballero López, Jesús; Sáez de Tejada, Anna; Ruiz Rodríguez, Juan Carlos; Ruiz Sanmartin, Adolfo; Rello, Jordi; Vellido Alcacena, Alfredo (Springer, 2012)
      Capítol de llibre
      Accés restringit per política de l'editorial