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Big Data & Bioengineering

Beruete Díaz

Miguel
‘We go beyond natural limits to obtain ultrasensitive sensors’
Miguel Beruete Díaz

•    Ganador de los “Publons Peer Review Awards 2018” en: Physics 
•    Ganador de los “Publons Peer Review Awards 2018” en: Multidisciplinary
•    Premio al mejor papel en fotónica (“Best photonic paper”) "12th International Congress on Artificial Materials for Novel Wave Phenomena, Metamaterials2018" por el papel "Controlling Photon Statistics with Arrays of Quantum Emitters”.

Área de investigación
Unidad o grupo de investigación
Tesis en curso

Codirectores: Miguel Beruete e Iñigo Ederra
Universidad: Public University of Navarre 
Facultad/escuela: Escuela Técnica Superior de Ingenieros Industriales y de Telecomunicación
Año:      Calificación:

Tipo de investigador
Vídeo
La invisibilidad a la vista
Miguel
Beruete Díaz
Head of the Unit
Navarrabiomed
Tipo de investigación
Unidad de investigación
Tesis dirigidas defendidas
Dayan Pérez Quintana
Diseño de antenas de banda de terahercio basadas en metasuperficies.
Alexia Moreno Peñarrubia
Aplicación de la tecnología de sub-milimétricas y THz en espectroscopia y generación de imágenes en los sectores aeroespacial, seguridad, bio, médico, agro y farmacéutico.
Unai Beaskoetxea Gartzia
Leaky Wave Antennas, Plasmonics and Metamaterials in the Terahertz.
Pablo Rodríguez Ulibarri
Metamaterials and Extraordinary Transmission structures applied to microwave, millimeter and terahertz waves devices.
Bakhtiyar Orazbayev
Advanced metamaterials for high resolution focusing and invisibility cloaks.
Víctor Pacheco Peña
Metamaterials and Plasmonics applied to devices on periodic structures at high frequencies: Microwaves, Terahertz and Optical range.
Víctor Torres Landívar
Plasmonics and Metamaterials at Terahertz Frequencies.
Miguel Navarro-Cía
Extraordinary transmission and geometrically-induced modes for metamaterials: from underlying physics to technological applications.

Multispectral biosensing

Multispectral biosensing

The team do research mainly on highly sensitive sensor and technical platforms for thin-film and biological substance characterisation using metamaterials, metasurfaces and plasmonic structures. The characterisation is multispectral, that is, it covers the entire infrared spectrum, from the terahertz band or far infrared to the visible infrared, including mid infrared and near infrared.

Investigador principal
Área de investigación
Big Data & Bioengineering
Thin-film and biological substance characterisation
Vídeo
La invisibilidad a la vista. El investigador de Navarrabiomed y Universidad Pública de Navarra Miguel Beruete explica en 'Teknopolis'(EITB) cómo convertir un objeto en invisible.
Miguel
Beruete Díaz
Head of the Unit
Colaboradores/as
Ederra Urzainqui, Iñigo
Navarrabiomed-Universidad Pública de Navarra
Liberal Olleta, Iñigo
Navarrabiomed-Universidad Pública de Navarra
Unidad de investigación / Grupo Vinculado
Contacto
Multispectral biosensing

Navarrabiomed - Centro de investigación biomédica
Complejo Hospitalario de Navarra, edificio de investigación.
Calle Irunlarrea, 3. 31008 Pamplona, Navarra, España. 

Algebra and Applications

Algebra and Applications

The Algebra and Applications multidisciplinary research team is made up of mathematicians and telecommunications engineers. At present, their lines of research are centred on the development of theoretical methods for gathering information based on data from different sources. They develop techniques and algorithms that are used in fields such as biomedical data classification, medical decision making, and evaluation and classification of movements in people with motor disabilities or the elderly.

Lines of research:

  • Machine-learning methods for multimodal information extraction.
  • Multimodal analysis of human movement. Application to rehabilitation and functional capacity improvement.
  • Techniques for optimising information extraction from clinical signs obtained with non-invasive techniques.
  • Group theory. Aggregation and engagement: application to data classification and decision-making under uncertainty.
Investigador principal
Área de investigación
Big Data & Bioengineering
Algebra and Applications
Colaboraciones Logotipos
Vídeo
Visor 360º
Colaboradores/as
Lecumberri Villamediana, Pablo
Universidad Pública de Navarra
Martínez Ramírez, Alicia
Universidad Pública de Navarra
Millor Muruzabal, Nora
Universidad Pública de Navarra
Uzqueda Esteban, Itziar
Universidad Pública de Navarra
Vidaurre Arbizu, Carmen
Universidad Pública de Navarra
Unidad de investigación / Grupo Vinculado
Contacto
Algebra and Applications

Navarrabiomed - Centro de investigación biomédica
Complejo Hospitalario de Navarra, edificio de investigación.
Calle Irunlarrea, 3. 31008 Pamplona, Navarra, España. 

Translational bioinformatics

Translational bioinformatics

Since the emergence of high tech, biomedical research has benefited from the so-called data revolution. Technological advancements have facilitated the acquisition and measurement of many biological characteristics and regulation levels in cellular environments and diseases. Its potential can only keep on growing. However, the data revolution also poses numerous challenges in the area of data analysis.

The Bioinformatics Unit faces two of these challenges:

  • Multi-omic data integration. While every researcher is integrating data, the goal is to assess how to address, through integration tools, questions about basic and clinical research. To this end, the Unit is developing new tools whenever required. In addition, the team are studying the best ways to use and combine the tools available and, most importantly, they are developing guides. Some of these tools and frameworks can be found in the STATegra Bioconductor package.
     
  • Translational medicine applications. The goal is to develop tools for relevant clinical questions such as patient heterogeneity. The Bioinformatics team use omic data and records to accurately identify patient subgroups that may have prognostic value. In addition, they try to understand disease evolution based on clinical and omic data.
Área de investigación
Big Data & Bioengineering
Bioinformatics
Actualidad

The DECISION project – European researchers seek to reduce the number of patients dying from cirrhosis

Author
Navarrabiomed
  • 21 European institutions join forces to tackle end-stage liver disease and liver failure with a systems medicine approach
  • Navarrabiomed-FMS takes part in the project through the Traslational Bioinformatics Unit.
     

Despite a vast array of available interventions and medications, more than 1 million people die of chronic liver disease (cirrhosis) per year worldwide, when the disease progresses to decompensated cirrhosis and acute-on-chronic liver failure (ACLF), a state in which the dysfunctional liver induces failure of other organs.

Following an acute decompensation of cirrhosis, 14% of the patients die of ACLF within 3 months. The reason why certain patients die and others survive is unknown, but huge differences between patients with regard to their individual genetics, medical history, precipitating events, clinical presentation and treatment response are suspected.

These individual differences call for personalised treatments based on a precise understanding of underlying mechanisms. Systems medicine and high-throughput technology nowadays allow for highly efficient analysis, integration, and predictive modelling of clinical data to develop the best fitted, most personalised treatment for each patient.

Over the next 5.5 years, the DECISION research consortium will analyse and integrate data from already existing clinical data and biological samples from 2,200 patients with cirrhosis at more than 8,600 time points to identify novel combinatorial therapies, validate them in animal models, and then test the most promising combinatorial therapy in a clinical trial.

The overall aim of the DECISION project is to prevent ACLF and to significantly reduce the mortality rate amongst patients with decompensated cirrhosis. The project receives 6 million € funding from the European Commission.
 

Categoría
Documentación

King's College London and Navarrabiomed provide insights into the relevance of the oral cavity in the antibiotic resistance process  

Author
Navarrabiomed

The research has been conducted by PhD student Victoria Carr and co-led by Dr David Moyes, King´s College London and Dr David Gómez Cabrero, Navarrabiomed

The results have been published by Nature Communications journal

 

Dr David Gómez Cabrero, head of the Translational Bioinformatics Unit of Navarrabiomed, recently published with professionals at King's College London the results of an investigation that focuses on the characterization of antibiotic resistance within the oral cavity. The results of the study, carried out in 2017-2020, have recently been published in the journal Nature Communications and represent a significant advance in our understanding of antibiotic resistance and its relationship with the oral microbiome.
 
The generation of antibiotic resistance by certain microorganisms - including bacteria - is a global healthcare threat. To understand the process of antibiotic resistance acquisition, databases of the genes that drive this resistance have been generated (the profile of these genes is known as the “resistome”). Despite the high prevalence of microorganisms in the human oral cavity, until now, the study of the resistome in the mouth has been limited.
 
The research carried out at King's College London, and Navarrabiomed has thoroughly analyzed the oral resistome in 788 worldwide samples; furthermore, the oral resistome was also compared with the intestine resistome (derived from stool sample analysis). The combination of microbial DNA sequencing techniques and their bioinformatic analysis have allowed the identification of differences associated with the country of origin and their location within the oral cavity.
 
Specifically, differences in the prevalence of genes, classes and mechanisms of antibiotic resistance have been observed. For example, it has been shown that although there is a smaller range of different antibiotic resistance genes in the oral cavity, the prevalence of specific antibiotic resistance genes is higher than in the gut. Likewise, similarities in the resistome between saliva samples and faeces from the same individuals have been identified and shown to be less than similarities between the oral cavity of two separate individuals.
 
The study highlights the importance of characterizing the resistome in various regions of the human body to discover the potential for antibiotic resistance in each area and to what extent it affects the use of antibiotics in the clinical context.

Categoría
Galería de imágenes
David Gómez Cabrero, Translational Bioinformatics Unit.
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Documentación
Vídeo
Unidad de investigación / Grupo Vinculado
Contacto
Bioinformatics

Navarrabiomed - Centro de investigación biomédica
Complejo Hospitalario de Navarra, edificio de investigación.
Calle Irunlarrea, 3. 31008 Pamplona, Navarra, España.  

Artificial Intelligence and Probabilistic Reasoning

Artificial Intelligence and Probabilistic Reasoning

The Artificial Intelligence and Approximate Reasoning Group (GIARA) was established in 2002 by Professor Humberto Bustince at the Public University of Navarra. Currently, GIARA is made of eighteen members (twelve holding doctoral degrees and five doctoral students).
GIARA is a multidisciplinary team (physicists, mathematicians, computer engineers and industrial engineers) with broad experience and a remarkable national and international impact. They conduct theoretical research in the areas of information fusion, fuzzy sets and extensions. In addition, they develop models and applications in the fields of data mining, big data and image processing.

Lines of research:

  • Theory: information fusion, fuzzy sets and extensions.
  • Decision making: multicriteria, consensus, preference relations and recommendation systems.
  • Computer vision: image processing, magnification/demagnification, edge detection, stereo vision.
  • Data mining: machine learning, classification, fuzzy rule-based models, ensemble-based models, deep learning, big data.
     
Investigador principal
Área de investigación
Big Data & Bioengineering
GIARA
Colaboradores/as
Antunes Dos Santos, Felipe
Navarrabiomed - Universidad Pública de Navarrra
Barrenechea Tartas, Edurne
Navarrabiomed - Universidad Pública de Navarrra
Burusco Juandeaburre, Ana Jesús
Navarrabiomed - Universidad Pública de Navarrra
De Miguel Turullols, Laura
Navarrabiomed - Universidad Pública de Navarrra
Dendarieta Sarries, Xabier
Navarrabiomed
Elkano Ilintxeta, Mikel
Navarrabiomed - Universidad Pública de Navarrra
Fernández Fernández, Francisco Javier
Navarrabiomed - Universidad Pública de Navarrra
Galar Idoate, Mikel
Navarrabiomed - Universidad Pública de Navarrra
Guerra Errea, Carlos
Navarrabiomed - Universidad Pública de Navarrra
Hernández Jaso, Ignacio
Navarrabiomed - Universidad Pública de Navarra
Iglesias Rey, Sara
Navarrabiomed - Universidad Pública de Navarrra
Jurío Munarriz, María Aránzazu
Navarrabiomed - Universidad Pública de Navarrra
López Molina, Carlos
Navarrabiomed - Universidad Pública de Navarrra
Lucca, Giancarlo
Navarrabiomed - Universidad Pública de Navarrra
Marco Detchart, Cedric
Navarrabiomed - Universidad Pública de Navarrra
Orduna Urrutia, Raúl
Navarrabiomed - Universidad Pública de Navarrra
Pagola Barrio, Miguel
Navarrabiomed - Universidad Pública de Navarrra
Paternain Dallo, Daniel
Navarrabiomed - Universidad Pública de Navarrra
Sanz Delgado, José Antonio
Navarrabiomed - Universidad Pública de Navarrra
Sesma Sara, Mikel
Navarrabiomed - Universidad Pública de Navarrra
Uriz Martín, Mikel Xabier
Navarrabiomed - Universidad Pública de Navarrra
Unidad de investigación / Grupo Vinculado
Contacto
Artificial Intelligence and Probabilistic Reasoning

Navarrabiomed - Centro de investigación biomédica
Complejo Hospitalario de Navarra, edificio de investigación.
Calle Irunlarrea, 3. 31008 Pamplona, Navarra, España. 

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