Listar GI-RNASA - Artigos por autor "Munteanu, Cristian-Robert"
Mostrando ítems 41-50 de 50
-
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 ... -
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 compound-target interaction using several artificial intelligence algorithms and comparison with a consensus-based strategy
Jimenes-Vargas, Karina; Pazos, A.; Munteanu, Cristian-Robert; Pérez-Castillo, Yunierkis; Tejera, Eduardo (BMC, 2024-03-07)[Absctract]: For understanding a chemical compound’s mechanism of action and its side effects, as well as for drug discovery, it is crucial to predict its possible protein targets. This study examines 15 developed ... -
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 ... -
Random Forest Classification Based on Star Graph Topological Indices for Antioxidant Proteins
Fernández-Blanco, Enrique; Aguiar-Pulido, Vanessa; Munteanu, Cristian-Robert; Dorado, Julián (Elsevier, 2012-10-29)[Abstract] Aging and life quality is an important research topic nowadays in areas such as life sciences, chemistry, pharmacology, etc. People live longer, and, thus, they want to spend that extra time with a better quality ... -
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 ... -
SNOMED2HL7: a tool to normalize and bind SNOMED CT concepts to the HL7 Reference Information Model
Pérez-Rey, David; Alonso-Calvo, Raúl; Paraíso-Medina, Sergio; Munteanu, Cristian-Robert; García-Remesal, Miguel (Elsevier, 2017-10)[Abstract] BACKGROUND: Current clinical research and practice requires interoperability among systems in a complex and highly dynamic domain. There has been a significant effort in recent years to develop integrative common ... -
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 ...