Angela Lopez-del Rio
Polytechnic University of Catalonia
Deep learningAlgorithmMachine learningBenchmark (computing)ResamplingArtificial intelligenceVirologyData structureQuantitative structure–activity relationshipPaddingCode (cryptography)Test setSchema (psychology)GeneralizationScheme (programming language)Cross-validationIn silicoSequence (medicine)MalariaIon pumpActivity classificationDeep neural networksSequenceComputer sciencePredictive modellingAmino acidTraining setInfectious disease (medical specialty)Parasite hostingCluster analysisLigand binding assayBiologyRelevance (information retrieval)
6Publications
1H-index
9Citations
Publications 5
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#1Angela Lopez-del Rio (UPC: Polytechnic University of Catalonia)H-Index: 1
#2Sergio Picart-Armada (UPC: Polytechnic University of Catalonia)H-Index: 5
Last. Alexandre Perera-Lluna (UPC: Polytechnic University of Catalonia)H-Index: 12
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In silico analysis of biological activity data has become an essential technique in pharmaceutical development. Specifically, the so-called proteochemometric models aim to share information between targets in machine learning ligand-target activity prediction models. However, bioactivity data sets used in proteochemometric modeling are usually imbalanced, which could potentially affect the performance of the models. In this work, we explored the effect of different balancing strategies in deep l...
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#1Angela Lopez-del Rio (UPC: Polytechnic University of Catalonia)H-Index: 1
#2Maria Jesus Martin (EMBL-EBI: European Bioinformatics Institute)H-Index: 41
Last. Rabie Saidi (EMBL-EBI: European Bioinformatics Institute)H-Index: 11
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The use of raw amino acid sequences as input for deep learning models for protein functional prediction has gained popularity in recent years. This scheme obliges to manage proteins with different lengths, while deep learning models require same-shape input. To accomplish this, zeros are usually added to each sequence up to a established common length in a process called zero-padding. However, the effect of different padding strategies on model performance and data structure is yet unknown. We p...
1 CitationsSource
#2Maria Jesus MartinH-Index: 41
Last. Rabie SaidiH-Index: 11
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Last. Alexandre Perera-Lluna (UPC: Polytechnic University of Catalonia)H-Index: 12
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Binding prediction between targets and drug-like compounds through deep neural networks has generated promising results in recent years, outperforming traditional machine learning-based methods. However, the generalization capability of these classification models is still an issue to be addressed. In this work, we explored how different cross-validation strategies applied to data from different molecular databases affect to the performance of binding prediction proteochemometrics models. These ...
9 CitationsSource
Last. Melchor Sanchez-MartinezH-Index: 11
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Malaria is a mosquito-borne infectious disease caused by parasitic protozoans of the genus Plasmodium. [...]
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