Mostrando ítems 51-55 de 192

    • pRIblast: A highly efficient parallel application for comprehensive lncRNA–RNA interaction prediction 

      Amatria Barral, Iñaki; González-Domínguez, Jorge; Touriño, Juan (Elsevier, 2023-01)
      [Abstract]: Long non-coding RNAs (lncRNAs) play a key role in several biological processes and scientists are constantly trying to come up with new strategies to elucidate their functions. One common approach to characterize ...
    • SparkEC: speeding up alignment-based DNA error correction tools 

      Expósito, Roberto R.; Martínez-Sánchez, Marco; Touriño, Juan (BioMed Central (Springer), 2022)
      [Abstract]: In recent years, huge improvements have been made in the context of sequencing genomic data under what is called Next Generation Sequencing (NGS). However, the DNA reads generated by current NGS platforms are ...
    • Non-IID data and Continual Learning processes in Federated Learning: A long road ahead 

      Criado, Marcos F.; Casado, Fernando E.; Iglesias Rodríguez, Roberto; Regueiro, Carlos V.; Barro, Senén (Elsevier, 2022)
      [Abstract] Federated Learning is a novel framework that allows multiple devices or institutions to train a machine learning model collaboratively while preserving their data private. This decentralized approach is prone ...
    • Parallel ant colony optimization for the training of cell signaling networks 

      González, Patricia; Prado-Rodriguez, Roberto; Gábor, Attila; Saez-Rodriguez, Julio; Banga, Julio R.; Doallo, Ramón (Elsevier, 2022)
      [Abstract]: Acquiring a functional comprehension of the deregulation of cell signaling networks in disease allows progress in the development of new therapies and drugs. Computational models are becoming increasingly popular ...
    • Incremental Learning from Low-labelled Stream Data in Open-Set Video Face Recognition 

      López-López, Eric; Pardo, Xosé Manuel; Regueiro, Carlos V. (Elsevier, 2022)
      [Abstract] Deep Learning approaches have brought solutions, with impressive performance, to general classification problems where wealthy of annotated data are provided for training. In contrast, less progress has been ...