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Stochastic molecular descriptors for polymers. 4. Study of complex mixtures with topological indices of mass spectra spiral and star networks: The blood proteome case
ArticleAbstract: The Quantitative Structure-Property Relationships (QSPRs) based on Graph or Network Theory are imporPalabras claves:Biopolymers mixtures, complex networks, QSPRAutores:Borges F., Chou K.C., González‐díaz H., Maykel Cruz-Monteagudo, Munteanu C.R., Natalia Dias Soeiro Cordeiro M., Uriarte E.Fuentes:scopusChromosome Gene Orientation Inversion Networks (GOINs) of Plasmodium Proteome
ArticleAbstract: The spatial distribution of genes in chromosomes seems not to be random. For instance, only 10% of gPalabras claves:chromosome microstructure, complex networks, gene orientation, Machine Learning, MALARIA, Plasmodium sp. proteomeAutores:Bernabé Ortega-Tenezaca, González‐díaz H., Quevedo‐tumailli V.Fuentes:scopusComplex networks and machine learning: From molecular to social sciences
OtherAbstract: Combining complex networks analysis methods with machine learning (ML) algorithms have become a veryPalabras claves:Biological networks, clustering, complex networks, Connectome, Ensemble classification, Machine Learning, neural networks, Social and economic networks, Supervised and unsupervised learning, SUPPORT VECTOR MACHINES, Systems biology, TIME SERIESAutores:David Quesada, Duardo-Sanchez A., Fletcher T., González‐díaz H., Maykel Cruz-Monteagudo, Quesada D.Fuentes:scopusMachine Learning Study of Metabolic Networks vs ChEMBL Data of Antibacterial Compounds
ArticleAbstract: Antibacterial drugs (AD) change the metabolic status of bacteria, contributing to bacterial death. HPalabras claves:antibacterial compounds, CHEMBL, complex networks, Information Fusion, Machine Learning, multidrug-resistant, perturbation theoryAutores:Gerardo M. Casañola-Martin, González‐díaz H., Green J.R., Humbert González-Díaz, Karel Diéguez-Santana, Rasulev B., Roldán Torres GutiérrezFuentes:googlescopusHP-Lattice QSAR for dynein proteins: Experimental proteomics (2D-electrophoresis, mass spectrometry) and theoretic study of a Leishmania infantum sequence
ArticleAbstract: The toxicity and inefficacy of actual organic drugs against Leishmaniosis justify research projectsPalabras claves:2D-electrophoresis, BLAST, complex networks, Dyneins, HP-Lattice model, Leishmania infantum, Mass spectrometry, Parasites proteomics, QSAR, Sequence alignment, Spectral momentsAutores:Bolas-Fernández F., Chou K.C., Dea-Ayuela M.A., González‐díaz H., Meneses-Marcel A., Ubeira F.M., Yunierkis Perez-CastilloFuentes:googlescopusIfptml mapping of drug graphs with protein and chromosome structural networks vs. Pre‐clinical assay information for discovery of antimalarial compounds
ArticleAbstract: The parasite species of genus Plasmodium causes Malaria, which remains a major global health problemPalabras claves:Antimalarial compounds, CHEMBL, complex networks, Machine Learning, NCBI‐GDV, perturbation theory, Plasmodium proteome, UniProtAutores:Bernabé Ortega-Tenezaca, González‐díaz H., Quevedo‐tumailli V.Fuentes:scopusQSAR, complex networks, principal components and partial order analysis of drug cardiotoxicity with proteome mass-spectra topological indices
Book PartAbstract: Blood Serum Proteome-Mass Spectra (SP-MS) may allow detecting Proteome-Early Drug Induced Cardiac ToPalabras claves:Clinical Proteomics, complex networks, Markov Model, Mass spectrometry, Partial Order, Quantitative Structure-Property RelationshipAutores:Borges F., Concud R., González‐díaz H., Maykel Cruz-Monteagudo, Munteanu C.R., Natalia Dias Soeiro Cordeiro M.Fuentes:scopusQSPR and Flow Cytometry Analysis (QSPR-FCA): Review and New Findings on Parallel Study of Multiple Interactions of Chemical Compounds with Immune Cellular and Molecular Targets
ReviewAbstract: The immune system helps to halt the infections caused by pathogenic microbial and parasitic agents.Palabras claves:CD19 lymphocytes, CHEMBL, complex networks, Drug immunotoxicity, Flow cytometry, Markov chains, perturbation theory, Spectral momentsAutores:Alejandro Speck-Planche, González‐díaz H., Luan F., Natalia Dias Soeiro Cordeiro M., Ramirez F.R., Tenorio-Borroto E.Fuentes:scopusMulti-target QSPR assemble of a Complex Network for the distribution of chemicals to biphasic systems and biological tissues
ArticleAbstract: Chemometrics, that based prediction on the probability of chemical distribution to different systemsPalabras claves:antibacterial compounds, Antimicrobial drugs, complex networks, Markov chains, Partition coefficient, QSPR, Spectral moments, tissue distribution, topological indicesAutores:Agüero-Chapin G., Castañeda-Cancio N., del Río M., González‐díaz H., Maykel Cruz-Monteagudo, Pérez M.A.C., Uriarte E.Fuentes:scopusPredicting metabolic reaction networks with Perturbation-Theory Machine Learning (PTML) models
ArticleAbstract: Background: Checking the connectivity (structure) of complex Metabolic Reaction Networks (MRNs) modePalabras claves:Combinatorial perturbation theory models, complex networks, Linear invariants, Machine Learning, Markov chains, Metabolic pathwaysAutores:Gerardo M. Casañola-Martin, González‐díaz H., Green J.R., Karel Diéguez-Santana, Rasulev B.Fuentes:googlescopus