Cheminformatics Perturbation-Theory Machine Learning Laboratory
CHEM PTML
Universidade da Coruña
La Coruña, EspañaPublications in collaboration with researchers from Universidade da Coruña (62)
2024
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From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine
Health Information Science and Systems, Vol. 12, Núm. 1
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MATEO: intermolecular α-amidoalkylation theoretical enantioselectivity optimization. Online tool for selection and design of chiral catalysts and products
Journal of Cheminformatics, Vol. 16, Núm. 1
2022
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Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2-Acylpyrrole Derivatives
Journal of chemical information and modeling, Vol. 62, Núm. 16, pp. 3928-3940
2021
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Ifptml mapping of drug graphs with protein and chromosome structural networks vs. Pre‐clinical assay information for discovery of antimalarial compounds
International Journal of Molecular Sciences, Vol. 22, Núm. 23
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Palladium-mediated synthesis and biological evaluation of C-10b substituted Dihydropyrrolo[1,2-b]isoquinolines as antileishmanial agents
European Journal of Medicinal Chemistry, Vol. 220
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Prediction of anti-glioblastoma drug-decorated nanoparticle delivery systems using molecular descriptors and machine learning
International Journal of Molecular Sciences, Vol. 22, Núm. 21
2020
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A multi-objective approach for anti-osteosarcoma cancer agents discovery through drug repurposing
Pharmaceuticals, Vol. 13, Núm. 11, pp. 1-16
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Gene prioritization through consensus strategy, enrichment methodologies analysis, and networking for osteosarcoma pathogenesis
International Journal of Molecular Sciences, Vol. 21, Núm. 3
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MCDcalc: Markov chain molecular descriptors calculator for medicinal chemistry
Current Topics in Medicinal Chemistry, Vol. 20, Núm. 4, pp. 305-317
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Net-net autoML selection of artificial neural network topology for brain connectome prediction
Applied Sciences (Switzerland), Vol. 10, Núm. 4
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OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine
Scientific Reports, Vol. 10, Núm. 1
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Perturbation-theory machine learning (PTML) multilabel model of the CheMBL dataset of preclinical assays for antisarcoma compounds
ACS Omega, Vol. 5, Núm. 42, pp. 27211-27220
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Prediction of antimalarial drug-decorated nanoparticle delivery systems with random forest models
Biology, Vol. 9, Núm. 8, pp. 1-15
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Prediction of breast cancer proteins involved in immunotherapy, metastasis, and RNA-binding using molecular descriptors and artificial neural networks
Scientific Reports, Vol. 10, Núm. 1
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Ptml multi-label algorithms: Models, software, and applications
Current Topics in Medicinal Chemistry, Vol. 20, Núm. 25, pp. 2326-2337
2019
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PTML Model of Enzyme Subclasses for Mining the Proteome of Biofuel Producing Microorganisms
Journal of Proteome Research, Vol. 18, Núm. 7, pp. 2735-2746
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Perturbation Theory Machine Learning Modeling of Immunotoxicity for Drugs Targeting Inflammatory Cytokines and Study of the Antimicrobial G1 Using Cytometric Bead Arrays
Chemical Research in Toxicology, Vol. 32, Núm. 9, pp. 1811-1823
2018
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Chromosome Gene Orientation Inversion Networks (GOINs) of Plasmodium Proteome
Journal of Proteome Research, Vol. 17, Núm. 3, pp. 1258-1268
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Gene prioritization, communality analysis, networking and metabolic integrated pathway to better understand breast cancer pathogenesis
Scientific Reports, Vol. 8, Núm. 1
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Net-Net Auto Machine Learning (AutoML) Prediction of Complex Ecosystems
Scientific Reports, Vol. 8, Núm. 1