Sergio Picart-Armada
Polytechnic University of Catalonia
AlgorithmParametric statisticsMachine learningDisease gene identificationMetabolomeKEGGArtificial intelligencePattern recognitionEnzymeChemistryMetabolic pathwayBiological dataNull (SQL)Protein function predictionMetabolomicsContext (language use)Biological networkMulti layerR packageMetabolomics dataNetwork analysisComputer scienceLipid metabolismPython (programming language)Interaction networkComputational biologyCluster analysisDrug discoveryIdentification (information)Benchmarking
18Publications
6H-index
117Citations
Publications 12
Newest
#2Pol Solà-Santos (UPC: Polytechnic University of Catalonia)
Last. Alexandre Perera-Lluna (UPC: Polytechnic University of Catalonia)H-Index: 13
view all 6 authors...
Untargeted metabolomics using liquid chromatography coupled to mass spectrometry (LC-MS) allows the detection of thousands of metabolites in biological samples. However, LC-MS data annotation is still considered a major bottleneck in the metabolomics pipeline since only a small fraction of the metabolites present in the sample can be annotated with the required confidence level. Here, we introduce mWISE (metabolomics wise inference of speck entities), an R package for context-based annotation of...
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#1Sergio Picart-Armada (UPC: Polytechnic University of Catalonia)H-Index: 6
#2Wesley K. ThompsonH-Index: 70
Last. Alexandre Perera-Lluna (UPC: Polytechnic University of Catalonia)H-Index: 13
view all 4 authors...
MOTIVATION Network diffusion and label propagation are fundamental tools in computational biology, with applications like gene-disease association, protein function prediction and module discovery. More recently, several publications have introduced a permutation analysis after the propagation process, due to concerns that network topology can bias diffusion scores. This opens the question of the statistical properties and the presence of bias of such diffusion processes in each of its applicati...
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#1Josep Marín-Llaó (Fraunhofer Society)H-Index: 3
#2Sarah Mubeen (Fraunhofer Society)H-Index: 5
Last. Daniel Domingo-Fernández (Fraunhofer Society)H-Index: 11
view all 6 authors...
SUMMARY High-throughput screening yields vast amounts of biological data which can be highly challenging to interpret. In response, knowledge-driven approaches emerged as possible solutions to analyze large datasets by leveraging prior knowledge of biomolecular interactions represented in the form of biological networks. Nonetheless, given their size and complexity, their manual investigation quickly becomes impractical. Thus, computational approaches, such as diffusion algorithms, are often emp...
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#1Angela Lopez-del Rio (UPC: Polytechnic University of Catalonia)H-Index: 2
#2Sergio Picart-Armada (UPC: Polytechnic University of Catalonia)H-Index: 6
Last. Alexandre Perera-Lluna (UPC: Polytechnic University of Catalonia)H-Index: 13
view all 3 authors...
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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#1Sergio Picart-Armada (UPC: Polytechnic University of Catalonia)H-Index: 6
#2Wesley K. Thompson (UCSD: University of California, San Diego)H-Index: 70
Last. Alexandre Perera-Lluna (UPC: Polytechnic University of Catalonia)H-Index: 13
view all 4 authors...
Motivation: Network diffusion and label propagation are fundamental tools in computational biology, with applications like gene-disease association, protein function prediction and module discovery. More recently, several publications have introduced a permutation analysis after the propagation process, due to concerns that network topology can bias diffusion scores. This opens the question of the statistical properties and the presence of bias of such diffusion processes in each of its applicat...
Source
#1Sergio Picart-Armada (UPC: Polytechnic University of Catalonia)H-Index: 6
#2Steven J. BarrettH-Index: 2
Last. Benoit H. DessaillyH-Index: 18
view all 6 authors...
In-silico identification of potential target genes for disease is an essential aspect of drug target discovery. Recent studies suggest that successful targets can be found through by leveraging genetic, genomic and protein interaction information. Here, we systematically tested the ability of 12 varied algorithms, based on network propagation, to identify genes that have been targeted by any drug, on gene-disease data from 22 common non-cancerous diseases in OpenTargets. We considered two biolog...
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#1Haizea Ziarrusta (Stockholm University)H-Index: 10
#2Anton Ribbenstedt (Stockholm University)H-Index: 5
Last. Nestor Etxebarria (UPV/EHU: University of the Basque Country)H-Index: 38
view all 11 authors...
The antidepressant amitriptyline is a widely used selective serotonin reuptake inhibitor that is found in the aquatic environment. The present study investigates alterations in the brain and the liver metabolome of gilt‐head bream (Sparus aurata) after exposure at an environmentally relevant concentration (0.2 µg/L) of amitriptyline for 7 d. Analysis of variance–simultaneous component analysis is used to identify metabolites that distinguish exposed from control animals. Overall, alterations in ...
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Case study with FELLA: a multi-omic mouse model of non-alcoholic fatty liver disease. (PDF 235 kb)
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#1Sergio Picart-Armada (UPC: Polytechnic University of Catalonia)H-Index: 6
#2Francesc Fernandez-Albert (UPC: Polytechnic University of Catalonia)H-Index: 7
Last. Alexandre Perera-Lluna (UPC: Polytechnic University of Catalonia)H-Index: 13
view all 5 authors...
Pathway enrichment techniques are useful for understanding experimental metabolomics data. Their purpose is to give context to the affected metabolites in terms of the prior knowledge contained in metabolic pathways. However, the interpretation of a prioritized pathway list is still challenging, as pathways show overlap and cross talk effects. We introduce FELLA, an R package to perform a network-based enrichment of a list of affected metabolites. FELLA builds a hierarchical representation of an...
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#1Haizea Ziarrusta (UPV/EHU: University of the Basque Country)H-Index: 10
#2Leire Mijangos (UPV/EHU: University of the Basque Country)H-Index: 10
Last. Olatz Zuloaga (UPV/EHU: University of the Basque Country)H-Index: 29
view all 10 authors...
Abstract The extensive use of the organic UV filter oxybenzone has led to its ubiquitous occurrence in the aquatic environment, causing an ecotoxicological risk to biota. Although some studies reported adverse effects, such as reproductive toxicity, further research needs to be done in order to assess its molecular effects and mechanism of action. Therefore, in the present work, we investigated metabolic perturbations in juvenile gilt-head bream (Sparus aurata) exposed over 14 days via the water...
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