Browsing RNASA-IMEDIR by Author "Porto-Pazos, Ana B."
Now showing items 1-4 of 4
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Artificial Neuron–Glia Networks Learning Approach Based on Cooperative Coevolution
Fernández-Blanco, Enrique; Cedrón, Francisco; Pazos, A.; Porto-Pazos, Ana B.; Mesejo, Pablo; Ibáñez, Oscar (World Scientific, 2015-04-06)[Abstract] Artificial Neuron–Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way ... -
Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications
Pastur-Romay, L.A.; Cedrón, Francisco; Pazos, A.; Porto-Pazos, Ana B. (MDPI, 2016-08-11)[Abstract] Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other ... -
Parallel computing for brain simulation
Pastur-Romay, L.A.; Porto-Pazos, Ana B.; Cedrón, Francisco; Pazos, A. (Bentham Science, 2017-05-01)[Abstract] Background: The human brain is the most complex system in the known universe, it is therefore one of the greatest mysteries. It provides human beings with extraordinary abilities. However, until now it has not ... -
Prediction of high anti-angiogenic activity peptides in silico using a generalized linear model and feature selection
Liñares Blanco, José; Porto-Pazos, Ana B.; Pazos, A.; Fernández-Lozano, Carlos (Nature, 2018-10-24)[Abstract] Screening and in silico modeling are critical activities for the reduction of experimental costs. They also speed up research notably and strengthen the theoretical framework, thus allowing researchers to ...
