Listar RNASA-IMEDIR por autor "Pazos, A."
Mostrando ítems 21-39 de 39
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Gene prioritization, communality analysis, networking and metabolic integrated pathway to better understand breast cancer pathogenesis
López-Cortés, Andrés; Paz-y-Miño, César; Cabrera-Andrade, Alejandro; Barigye, Stephen J.; Munteanu, Cristian-Robert; González-Díaz, Humberto; Pazos, A.; Pérez-Castillo, Yunierkis; Tejera, Eduardo (Nature, 2018-11-12)[Abstract] Consensus strategy was proved to be highly efficient in the recognition of gene-disease association. Therefore, the main objective of this study was to apply theoretical approaches to explore genes and communities ... -
Improvement of Epitope Prediction Using Peptide Sequence Descriptors and Machine Learning
Munteanu, Cristian-Robert; Gestal, M.; Martínez-Acevedo, Yunuen G.; Pazos, A.; Dorado, Julián; Pedreira Souto, Nieves (MDPI, 2019)[Abstract] In this work, we improved a previous model used for the prediction of proteomes as new B-cell epitopes in vaccine design. The predicted epitope activity of a queried peptide is based on its sequence, a known ... -
LECTINPred: web server that uses complex networks of protein structure for prediction of lectins with potential use as cancer biomarkers or in parasite vaccine design
Munteanu, Cristian-Robert; Pedreira Souto, Nieves; Dorado, Julián; Pazos, A.; Pérez-Montoto, Lázaro G.; Ubeira, Florencio; González-Díaz, Humberto (Wiley, 2014-03-18) -
Mapping chemical structure-activity information of HAART-drug cocktails over complex networks of AIDS epidemiology and socioeconomic data of U.S. counties
Herrera Ibatá, Diana María; Pazos, A.; Orbegozo-Medina, Ricardo Alfredo; Romero-Durán, Francisco Javier; González-Díaz, Humberto (Elsevier, 2015-04-24)[Abstract] Using computational algorithms to design tailored drug cocktails for highly active antiretroviral therapy (HAART) on specific populations is a goal of major importance for both pharmaceutical industry and public ... -
Microemulsions for colorectal cancer treatments: general considerations and formulation of methotrexate
Flores, Sergio E.; Rial-Hermida, M.Isabel; Ramírez, Jorge C.; Pazos, A.; Concheiro, Ángel; Álvarez-Lorenzo, Carmen; Peralta, René D. (Bentham, 2016-04-01)[Abstract] Microemulsions combine the advantages of emulsions with those of nanocarriers, overcoming the stability problems of the former and providing facile scalable systems with compartments adequate for high drug ... -
Net-net Auto machine learning (AutoML) prediction of complex ecosystems
Barreiro, Enrique; Munteanu, Cristian-Robert; Cruz-Monteagudo, Maykel; Pazos, A.; González-Díaz, Humberto (Nature, 2018-08-17)[Abstract] Biological Ecosystem Networks (BENs) are webs of biological species (nodes) establishing trophic relationships (links). Experimental confirmation of all possible links is difficult and generates a huge volume ... -
Net-Net AutoML Selection of Artificial Neural Network Topology for Brain Connectome Prediction
Barreiro, Enrique; Munteanu, Cristian-Robert; Gestal, M.; Rabuñal, Juan R.; Pazos, A.; González-Díaz, Humberto; Dorado, Julián (MDPI, 2020-02-14)[Abstract] Brain Connectome Networks (BCNs) are defined by brain cortex regions (nodes) interacting with others by electrophysiological co-activation (edges). The experimental prediction of new interactions in BCNs ... -
OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine
López-Cortés, Andrés; Paz-y-Miño, César; Guerrero, Santiago; Cabrera-Andrade, Alejandro; Munteanu, Cristian-Robert; González-Díaz, Humberto; Pazos, A.; Pérez-Castillo, Yunierkis; Tejera, Eduardo; Barigye, Stephen J. (Springer Nature, 2020-03-24)[Abstract] Breast cancer (BC) is the leading cause of cancer-related death among women and the most commonly diagnosed cancer worldwide. Although in recent years large-scale efforts have focused on identifying new therapeutic ... -
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 ... -
Perturbation theory/machine learning model of ChEMBL data for dopamine targets: docking, synthesis, and assay of new l-prolyl-l-leucyl-glycinamide peptidomimetics
Ferreira da Costa, Joana; Silva, David; Caamaño, Olga; Brea, José M.; Loza, María Isabel; Munteanu, Cristian-Robert; Pazos, A.; García-Mera, Xerardo; González-Díaz, Humberto (American Chemical Society, 2018-05-23)[Abstract] Predicting drug–protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning ... -
Perturbation-Theory Machine Learning (PTML) Multilabel Model of the ChEMBL Dataset of Preclinical Assays for Antisarcoma Compounds
Cabrera-Andrade, Alejandro; López-Cortés, Andrés; Munteanu, Cristian-Robert; Pazos, A.; Pérez-Castillo, Yunierkis; Tejera, Eduardo; Arrasate, Sonia; González-Díaz, Humberto (American Chemical Society, 2020-10-14)[Abstract] Sarcomas are a group of malignant neoplasms of connective tissue with a different etiology than carcinomas. The efforts to discover new drugs with antisarcoma activity have generated large datasets of multiple ... -
Population Subset Selection for the Use of a Validation Dataset for Overfitting Control in Genetic Programming
Rivero, Daniel; Fernández-Blanco, Enrique; Fernández-Lozano, Carlos; Pazos, A. (Taylor & Francis Group, 2019-07-31)[Abstract] Genetic Programming (GP) is a technique which is able to solve different problems through the evolution of mathematical expressions. However, in order to be applied, its tendency to overfit the data is one of ... -
Prediction of Breast Cancer Proteins Involved in Immunotherapy, Metastasis, and RNA-Binding Using Molecular Descriptors and Artifcial Neural Networks
López-Cortés, Andrés; Cabrera-Andrade, Alejandro; Vázquez-Naya, José; Pazos, A.; Gonzáles-Díaz, Humberto; Paz-y-Miño, César; Guerrero, Santiago; Pérez-Castillo, Yunierkis; Tejera, Eduardo; Munteanu, Cristian-Robert (Springer Nature, 2020-05-22)[Abstract] Breast cancer (BC) is a heterogeneous disease where genomic alterations, protein expression deregulation, signaling pathway alterations, hormone disruption, ethnicity and environmental determinants are involved. ... -
Prediction of high anti-angiogenic activity peptides in silico using a generalized linear model and feature selection
Liñares Blanco, Jose; 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 ... -
Prediction of Nucleoitide Binding Peptides Using Star Graph Topological Índices
Liu, Yong; Munteanu, Cristian-Robert; Fernández-Blanco, Enrique; Tan, Zhiliang; Santos-del-Riego, Antonino; Pazos, A. (Elsevier, 2015-08-05)[Abstract] The nucleotide binding proteins are involved in many important cellular processes, such as transmission of genetic information or energy transfer and storage. Therefore, the screening of new peptides for this ... -
Redesign and performance of an automatic segmentation method
Carballal, Adrián; Fernández-Lozano, Carlos; Nóvoa, Francisco; Rodríguez-Fernández, Nereida; Santos, Iria; García-Guimaraes, Marcos; Aldama López, Guillermo; Calviño-Santos, Ramón; Vázquez Rodríguez, José Manuel; Pazos, A. (MDPI, 2018-09-05)[Resumen] La información más relevante de las angiografías coronarias se extrae empleando técnicas de segmentación, que pueden ser automáticas, semiautomáticas o manuales. Existen numerosos algoritmos de segmentación ... -
Texture Analysis in Gel Electrophoresis Images Using an Integrative Kernel-Based Approach
Fernández-Lozano, Carlos; Seoane, José A.; Gestal, M.; Gaunt, Tom R.; Dorado, Julián; Pazos, A.; Campbell, Colin (Nature, 2016-01-13)[Abstract] Texture information could be used in proteomics to improve the quality of the image analysis of proteins separated on a gel. In order to evaluate the best technique to identify relevant textures, we use several ... -
UAV Swarm Path Planning With Reinforcement Learning for Field Prospecting
Puente-Castro, Alejandro; Rivero, Daniel; Pazos, A.; Fernández-Blanco, Enrique (Springer, 2022-03-03)[Abstract] There has been steady growth in the adoption of Unmanned Aerial Vehicle (UAV) swarms by operators due to their time and cost benefits. However, this kind of system faces an important problem, which is the ... -
Using Genetic Algorithms to Improve Support Vector Regression in the Analysis of Atomic Spectra of Lubricant Oils
Fernández-Lozano, Carlos; Cedrón, Francisco; Rivero, Daniel; Dorado, Julián; Andrade-Garda, José Manuel; Pazos, A.; Gestal, M. (Emerald, 2016-06)[Abstract] Purpose – The purpose of this paper is to assess the quality of commercial lubricant oils. A spectroscopic method was used in combination with multivariate regression techniques (ordinary multivariate ...