@article{domingueztesting,

title = {Testing the Performance, Adequacy, and Applicability of an Artificial Intelligent Model for Pediatric Pneumonia Diagnosis},

author = {Sara Domínguez-Rodríguez and Helena Liz López and Ángel Panizo-Lledot and Álvaro Ballesteros and Ron Dagan and David Greenberg and Lourdes Gutiérrez and Pablo Rojo and Enrique Otheo and Juan Carlos Galán and others},

year  = {2022},

date = {2022-05-27},

urldate = {2022-05-27},

keywords = {Health},

pubstate = {published},

tppubtype = {article}

}

@article{pathogens11060662,

title = {SARS-CoV-2 Mutant Spectra at Different Depth Levels Reveal an Overwhelming Abundance of Low Frequency Mutations},

author = {Brenda Martínez-González and María Eugenia Soria and Lucía Vázquez-Sirvent and Cristina Ferrer-Orta and Rebeca Lobo-Vega and Pablo Mínguez and Lorena Fuente and Carlos Llorens and Beatriz Soriano and Ricardo Ramos-Ruíz and Marta Cortón and Rosario López-Rodríguez and Carlos García-Crespo and Pilar Somovilla and Antoni Durán-Pastor and Isabel Gallego and Ana Isabel Ávila and Maria Soledad Delgado and Federico Morán and Cecilio López-Galíndez and Jordi Gómez and Luis Enjuanes and Llanos Salar-Vidal and Mario Esteban-Muñoz and Jaime Esteban and Ricardo Fernández-Roblas and Ignacio Gadea and Carmen Ayuso and Javier Ruíz-Hornillos and Nuria Verdaguer and Esteban Domingo and Celia Perales},

url = {https://www.mdpi.com/2076-0817/11/6/662},

doi = {10.3390/pathogens11060662},

issn = {2076-0817},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

journal = {Pathogens},

volume = {11},

number = {6},

abstract = {Populations of RNA viruses are composed of complex and dynamic mixtures of variant genomes that are termed mutant spectra or mutant clouds. This applies also to SARS-CoV-2, and mutations that are detected at low frequency in an infected individual can be dominant (represented in the consensus sequence) in subsequent variants of interest or variants of concern. Here we briefly review the main conclusions of our work on mutant spectrum characterization of hepatitis C virus (HCV) and SARS-CoV-2 at the nucleotide and amino acid levels and address the following two new questions derived from previous results: (i) how is the SARS-CoV-2 mutant and deletion spectrum composition in diagnostic samples, when examined at progressively lower cut-off mutant frequency values in ultra-deep sequencing; (ii) how the frequency distribution of minority amino acid substitutions in SARS-CoV-2 compares with that of HCV sampled also from infected patients. The main conclusions are the following: (i) the number of different mutations found at low frequency in SARS-CoV-2 mutant spectra increases dramatically (50- to 100-fold) as the cut-off frequency for mutation detection is lowered from 0.5% to 0.1%, and (ii) that, contrary to HCV, SARS-CoV-2 mutant spectra exhibit a deficit of intermediate frequency amino acid substitutions. The possible origin and implications of mutant spectrum differences among RNA viruses are discussed.},

keywords = {Health, Self-organizing map},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1128/Spectrum.01459-21,

title = {A Two-Level, Intramutant Spectrum Haplotype Profile of Hepatitis C Virus Revealed by Self-Organized Maps},

author = {Maria Soledad Delgado and Celia Perales and Carlos García-Crespo and María Eugenia Soria and Isabel Gallego and Ana Isabel Ávila and Brenda Martínez-González and Lucía Vázquez-Sirvent and Cecilio López-Galíndez and Federico Morán and Esteban Domingo and Benjamin W. Neuman},

doi = {10.1128/Spectrum.01459-21  URL = https://journals.asm.org/doi/abs/10.1128/Spectrum.01459-21},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Microbiology Spectrum},

volume = {9},

number = {3},

pages = {e01459-21},

abstract = {The study provides for the first time the haplotype profile and its variation in the course of its adaptation to a cell culture environment in the absence of external selective constraints. The deep sequencing-based self-organized maps document a two-layer haplotype distribution with an ample basal platform and a lower number of protruding peaks. RNA viruses replicate as complex mutant spectra termed viral quasispecies. The frequency of each individual genome in a mutant spectrum depends on its rate of generation and its relative fitness in the replicating population ensemble. The advent of deep sequencing methodologies allows for the first-time quantification of haplotype abundances within mutant spectra. There is no information on the haplotype profile of the resident genomes and how the landscape evolves when a virus replicates in a controlled cell culture environment. Here, we report the construction of intramutant spectrum haplotype landscapes of three amplicons of the NS5A-NS5B coding region of hepatitis C virus (HCV). Two-dimensional (2D) neural networks were constructed for 44 related HCV populations derived from a common clonal ancestor that was passaged up to 210 times in human hepatoma Huh-7.5 cells in the absence of external selective pressures. The haplotype profiles consisted of an extended dense basal platform, from which a lower number of protruding higher peaks emerged. As HCV increased its adaptation to the cells, the number of haplotype peaks within each mutant spectrum expanded, and their distribution shifted in the 2D network. The results show that extensive HCV replication in a monotonous cell culture environment does not limit HCV exploration of sequence space through haplotype peak movements. The landscapes reflect dynamic variation in the intramutant spectrum haplotype profile and may serve as a reference to interpret the modifications produced by external selective pressures or to compare with the landscapes of mutant spectra in complex in vivo environments. IMPORTANCE The study provides for the first time the haplotype profile and its variation in the course of virus adaptation to a cell culture environment in the absence of external selective constraints. The deep sequencing-based self-organized maps document a two-layer haplotype distribution with an ample basal platform and a lower number of protruding peaks. The results suggest an inferred intramutant spectrum fitness landscape structure that offers potential benefits for virus resilience to mutational inputs.},

keywords = {Data Projection, Health, Self-organizing map},

pubstate = {published},

tppubtype = {article}

}

@article{liz2021ensemblesb,

title = {Ensembles of Convolutional Neural Network models for pediatric pneumonia diagnosis},

author = {Helena Liz López and Manuel Sánchez-Monta nés and Alfredo Tagarro and Sara Domínguez-Rodríguez and Ron Dagan and David Camacho},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Future Generation Computer Systems},

volume = {122},

pages = {220--233},

publisher = {Elsevier},

keywords = {Health},

pubstate = {published},

tppubtype = {article}

}

@article{<LineBreak>	10261_210788,

title = {Morphology Clustering Software for AFM Images, Based on Particle Isolation and Artificial Neural Networks},

author = {Maria Soledad Delgado and Miguel Moreno and Luis Vázquez and José A. Martín-Gago and Carlos Briones},

doi = {10.1109/ACCESS.2019.2950984},

year  = {2019},

date = {2019-01-01},

urldate = {2019-01-01},

organization = {This work was supported in part by the Spanish Ministry of Economy and Competitiveness (MINECO) funded by the EU through the FEDER Programme under Grant BIO2016-79618-R and Grant MAT2017-85089-C2-1-R, in part by the Spanish State Research Agency (AEI) through the Unidad de Excelencia María de Maeztu-Centro de Astrobiología (CSIC-INTA) under Project MDM-2017-0737, and in part by the Comunidad de Madrid under Grant S2018/NMT-4349.},

abstract = {[EN] Advanced microscopy techniques currently allow scientists to visualize biomolecules at high resolution. Among them, atomic force microscopy (AFM) shows the advantage of imaging molecules in their native state, without requiring any staining or coating of the sample. Biopolymers, including proteins and structured nucleic acids, are flexible molecules that can fold into alternative conformations for any given monomer sequence, as exemplified by the different three-dimensional structures adopted by RNA in solution. Therefore, the manual analysis of images visualized by AFM and other microscopy techniques becomes very laborious and time-consuming (and may also be inadvertently biased) when large populations of biomolecules are studied. Here we present a novel morphology clustering software, based on particle isolation and artificial neural networks, which allows the automatic image analysis and classification of biomolecules that can show alternative conformations. It has been tested with a set of AFM images of RNA molecules (a 574 nucleotides-long functinal region of the hepatitis C virus genome that contains its internal ribosome entry site element) structured in folding buffers containing 0, 2, 4, 6 or 10 mM Mg. The developed software shows a broad applicability in the microscopy-based analysis of biopolymers and other complex biomolecules.},

keywords = {Clustering, Growing cell structures, Health, Self-organizing map},

pubstate = {published},

tppubtype = {article}

}

@article{Lorenzo-Redondo2014,

title = {Realistic Three Dimensional Fitness Landscapes Generated by Self Organizing Maps for the Analysis of Experimental HIV-1 Evolution},

author = {Ramón Lorenzo-Redondo and Maria Soledad Delgado and Federico Morán and Cecilio Lopez-Galindez},

url = {https://plos.figshare.com/articles/dataset/_Realistic_Three_Dimensional_Fitness_Landscapes_Generated_by_Self_Organizing_Maps_for_the_Analysis_of_Experimental_HIV_1_Evolution_/948357},

doi = {10.1371/journal.pone.0088579},

year  = {2014},

date = {2014-01-01},

urldate = {2014-01-01},

keywords = {Data Projection, Health, Self-organizing map},

pubstate = {published},

tppubtype = {article}

}

@article{article,

title = {Gait patterns in a reference dataset of healthy children},

author = {Maria Soledad Delgado and David Gómez and Irene Pulido-Valdeolivas and Javier Lopez and J. A. Martín and F. Morán and Estrella Rausell},

doi = {10.1016/j.gaitpost.2011.10.345},

year  = {2012},

date = {2012-01-01},

urldate = {2012-01-01},

journal = {Gait & Posture},

volume = {36},

pages = {S97},

keywords = {Data Analysis, Growing cell structures, Health, Self-organizing map},

pubstate = {published},

tppubtype = {article}

}