Listar por autor "González-Díaz, Humberto"
Mostrando ítems 21-33 de 33
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MI-NODES multiscale models of metabolic reactions, brain connectome, ecological, epidemic, world trade, and legal-social networks
Duardo-Sánchez, Aliuska; González-Díaz, Humberto; Pazos, A. (Bentham, 2015)[Abstract] Complex systems and networks appear in almost all areas of reality. We find then from proteins residue networks to Protein Interaction Networks (PINs). Chemical reactions form Metabolic Reactions Networks (MRNs) ... -
MIANN models in medicinal, physical and organic chemistry
González-Díaz, Humberto; Arrasate, Sonia; Sotomayor, Nuria; Lete, Esther; Munteanu, Cristian-Robert; Pazos, A.; Besada-Porto, Lina; Ruso, Juan M. (Bentham, 2013)[Abstract] Reducing costs in terms of time, animal sacrifice, and material resources with computational methods has become a promising goal in Medicinal, Biological, Physical and Organic Chemistry. There are many computational ... -
MIANN models of networks of biochemical reactions, ecosystems, and U.S. Supreme Court with Balaban-Markov indices
Duardo-Sánchez, Aliuska; González-Díaz, Humberto; Pazos, A. (Bentham Science, 2015)[Abstract] We can use Artificial Neural Networks (ANNs) and graph Topological Indices (TIs) to seek structure-property relationship. Balabans’ J index is one of the classic TIs for chemo-informatics studies. We used here ... -
Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors
Duardo-Sánchez, Aliuska; Munteanu, Cristian-Robert; Riera-Fernández, Pablo; López-Díaz, Antonio; Pazos, A.; González-Díaz, Humberto (American Chemical Society, 2013-12-08)[Abstract] The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein ... -
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 ... -
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 ... -
Prediction of Anti-Glioblastoma Drug-Decorated Nanoparticle Delivery Systems Using Molecular Descriptors and Machine Learning
Munteanu, Cristian-Robert; Gutiérrez-Asorey, Pablo; Blanes-Rodríguez, Manuel; Hidalgo-Delgado, Ismael; Blanco Liverio, María de Jesús; Galdo, Brais; Porto-Pazos, Ana B.; Gestal, M.; Arrasate, Sonia; González-Díaz, Humberto (MDPI, 2021)[Abstract] The theoretical prediction of drug-decorated nanoparticles (DDNPs) has become a very important task in medical applications. For the current paper, Perturbation Theory Machine Learning (PTML) models were built ... -
S2SNet: a tool for transforming characters and numeric sequences into star network topological indices in chemoinformatics, bioinformatics, biomedical, and social-legal sciences
Munteanu, Cristian-Robert; Magalhaes, Alexandre L.; Duardo-Sánchez, Aliuska; Pazos, A.; González-Díaz, Humberto (Bentham, 2013)[Abstract] The study of complex systems such as proteins/DNA/RNA or dynamics of tax law systems can be carried out with the complex network theory. This allows the numerical quantification of the significant information ... -
The Rücker–Markov invariants of complex bio-systems: applications in parasitology and neuroinformatics
González-Díaz, Humberto; Riera-Fernández, Pablo; Pazos, A.; Munteanu, Cristian-Robert (Elsevier, 2013-02-23)[Abstract] Rücker's walk count (WC) indices are well-known topological indices (TIs) used in Chemoinformatics to quantify the molecular structure of drugs represented by a graph in Quantitative structure–activity/property ... -
Web Server and R Library for the Calculation of Markov Chains Molecular Descriptors
Carracedo-Reboredo, Paula; Munteanu, Cristian-Robert; González-Díaz, Humberto; Fernández-Lozano, Carlos (MDPI AG, 2020-08-20){Abstract] Markov Chain Molecular Descriptors (MCDs) have been largely used to solve Cheminformatics problems. The software to perform the calculation is not always available for general users. In this work, we developed ...