Listar RNASA-IMEDIR por autor "Munteanu, Cristian-Robert"
Mostrando ítems 1-20 de 24
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A methodology for the design of experiments in computational intelligence with multiple regression models
Fernández-Lozano, Carlos; Gestal, M.; Munteanu, Cristian-Robert; Dorado, Julián; Pazos, A. (Peer J, 2016-12-01)[Abstract] The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the ... -
ANN multiscale model of anti-HIV Drugs activity vs AIDS prevalence in the US at county level based on information indices of molecular graphs and social networks
González-Díaz, Humberto; Herrera-Ibatá, Diana María; Duardo-Sánchez, Aliuska; Munteanu, Cristian-Robert; Orbegozo-Medina, Ricardo Alfredo; Pazos, A. (American Chemical Society, 2014)[Abstract] This work is aimed at describing the workflow for a methodology that combines chemoinformatics and pharmacoepidemiology methods and at reporting the first predictive model developed with this methodology. The ... -
Automatic Assessment of Alzheimer’s Disease Diagnosis Based on Deep Learning Techniques
Puente-Castro, Alejandro; Fernández-Blanco, Enrique; Pazos, A.; Munteanu, Cristian-Robert (Elsevier, 2020-05)[Abstract] Early detection is crucial to prevent the progression of Alzheimer’s disease (AD). Thus, specialists can begin preventive treatment as soon as possible. They demand fast and precise assessment in the diagnosis ... -
Bio-AIMS collection of chemoinformatics web tools based on molecular graph information and artificial intelligence models
Munteanu, Cristian-Robert; González-Díaz, Humberto; García, Rafael; Loza, Mabel; Pazos, A. (Bentham, 2015-09-01)[Abstract] The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction ... -
Carbon nanotubes’ effect on mitochondrial oxygen flux dynamics: polarography experimental study and machine learning models using star graph trace invariants of Raman spectra
González-Durruthy, Michael; Monserrat, José M.; Rasulev, Bakhtiyor; Casañola-Martín, Gerardo M.; Barreiro Sorrivas, José María; Paraíso-Medina, Sergio; Maojo, Víctor; González-Díaz, Humberto; Pazos, A.; Munteanu, Cristian-Robert (MDPI, 2017-11-11)[Abstract] This study presents the impact of carbon nanotubes (CNTs) on mitochondrial oxygen mass flux (Jm) under three experimental conditions. New experimental results and a new methodology are reported for the first ... -
Classification of mild cognitive impairment and Alzheimer’s Disease with machine-learning techniques using 1H Magnetic Resonance Spectroscopy data
Munteanu, Cristian-Robert; Fernández-Lozano, Carlos; Mato-Abad, Virginia; Pita-Fernández, Salvador; Álvarez-Linera, Juan; Hernández-Tamames, Juan Antonio; Pazos, A. (Elsevier, 2015-03-30)[Abstract] Several magnetic resonance techniques have been proposed as non-invasive imaging biomarkers for the evaluation of disease progression and early diagnosis of Alzheimer’s Disease (AD). This work is the first ... -
Decrypting strong and weak single-walled carbon nanotubes interactions with mitochondrial voltage-dependent anion channels using molecular docking and perturbation theory
González-Durruthy, Michael; Werhli, Adriano V.; Seus, Vinicius; Machado, Karina S.; Pazos, A.; Munteanu, Cristian-Robert; González-Díaz, Humberto; Monserrat, José M. (Nature, 2017-10-16)[Abstract] The current molecular docking study provided the Free Energy of Binding (FEB) for the interaction (nanotoxicity) between VDAC mitochondrial channels of three species (VDAC1-Mus musculus, VDAC1-Homo sapiens, ... -
Experimental and computational studies of fatty acid distribution networks
Liu, Yong; Buendía-Rodríguez, Germán; Peñuelas-Rivas, Claudia Giovanna; Tan, Zhiliang; Rivas-Guevara, María; Tenorio-Borroto, Esvieta; Munteanu, Cristian-Robert; Pazos, A.; González-Díaz, Humberto (Royal Society of Chemistry, 2015-08-06)[Abstract] Unbalanced uptake of Omega 6/Omega 3 (ω-6/ω-3) ratios could increase chronic disease occurrences, such as inflammation, atherosclerosis, or tumor proliferation, and methylation methods for measuring the ruminal ... -
Experimental Study and ANN Dual-Time Scale Perturbation Model of Electrokinetic Properties of Microbiota
Liu, Yong; Munteanu, Cristian-Robert; Fernández-Lozano, Carlos; Pazos, A.; Ran, Tao; Tan, Zhiliang; Zhou, Chuanshe; Tang, Shaoxun; González-Díaz, Humberto (Frontiers Science, 2017-06-30)[Abstract] The electrokinetic properties of the rumen microbiota are involved in cell surface adhesion and microbial metabolism. An in vitro study was carried out in batch culture to determine the effects of three levels ... -
Experimental study and random forest prediction model of microbiome cell surface hydrophobicity
Liu, Yong; Tang, Shaoxun; Fernández-Lozano, Carlos; Munteanu, Cristian-Robert; Pazos, A.; Yu, Yi-zun; Tan, Zhiliang; González-Díaz, Humberto (Elsevier, 2016-11-09)[Abstract] The cell surface hydrophobicity (CSH) is an assessable physicochemical property used to evaluate the microbial adhesion to the surface of biomaterials, which is an essential step in the microbial biofilm formation ... -
Experimental–computational study of carbon nanotube effects on mitochondrial respiration: in silico nano-QSPR machine learning models based on new Raman spectra transform with Markov–Shannon entropy invariants
González-Durruthy, Michael; Alberici, Luciane C.; Curti, Carlos; Naal, Zeki; Atique-Sawazaki, David T.; Vázquez-Naya, José; González-Díaz, Humberto; Munteanu, Cristian-Robert (ACS Publications, 2017-04-17)[Abstract] The study of selective toxicity of carbon nanotubes (CNTs) on mitochondria (CNT-mitotoxicity) is of major interest for future biomedical applications. In the current work, the mitochondrial oxygen consumption ... -
Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis
Cabrera-Andrade, Alejandro; López-Cortés, Andrés; Jaramillo-Koupermann, Gabriela; Paz-y-Miño, César; Pérez-Castillo, Yunierkis; Munteanu, Cristian-Robert; González-Díaz, Humberto; Pazos, A.; Tejera, Eduardo (M D P I AG, 2020-02-05)[Abstract] Osteosarcoma is the most common subtype of primary bone cancer, affecting mostly adolescents. In recent years, several studies have focused on elucidating the molecular mechanisms of this sarcoma; however, its ... -
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 ... -
General machine learning model, review, and experimental-theoretic study of magnolol activity in enterotoxigenic induced oxidative stress
Deng, Yanli; Liu, Yong; Tang, Shaoxun; Zhou, Chuanshe; Han, Xuefeng; Xiao, Wenjun; Pastur-Romay, L.A.; Vázquez-Naya, José; Pereira-Loureiro, Javier; Munteanu, Cristian-Robert; Tang, Zhiliang (Bentham Science, 2017)[Abstract] This study evaluated the antioxidative effects of magnolol based on the mouse model induced by Enterotoxigenic Escherichia coli (E. coli, ETEC). All experimental mice were equally treated with ETEC suspensions ... -
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) -
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 ...