Exploració per autor "Bosio, Mattia"
Ara es mostren els items 1-16 de 16
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A catalogue of 863 Rett-syndrome-causing MECP2 mutations and lessons learned from data integration
(Springer Nature, 2021)
Article
Accés obertRett syndrome (RTT) is a rare neurological disorder mostly caused by a genetic variation in MECP2. Making new MECP2 variants and the related phenotypes available provides data for better understanding of disease mechanisms ... -
Differential expression of long non-coding RNAs are related to proliferation and histological diversity in follicular lymphomas
(2018-01-01)
Article
Accés obertLong non-coding RNAs (lncRNAs) comprise a family of non-coding transcripts that are emerging as relevant gene expression regulators of different processes, including tumour development. To determine the possible contribution ... -
Ensemble learning and hierarchical data representation for microarray classification
(Institute of Electrical and Electronics Engineers (IEEE), 2013)
Text en actes de congrés
Accés restringit per política de l'editorialThe microarray data classification is an open and active research field. The development of more accurate algorithms is of great interest and many of the developed techniques can be straightforwardly applied in analyzing ... -
Examen Final
(Universitat Politècnica de Catalunya, 2013-06-25)
Examen
Accés restringit a la comunitat UPC -
Feature set enhancement via hierarchical clustering for microarray classification
(2011)
Text en actes de congrés
Accés restringit per política de l'editorialA new method for gene expression classification is proposed in this paper. In a first step, the original feature set is enriched by including new features, called metagenes, produced via hierarchical clustering. In a ... -
Gene expression data classification combining hierarchical representation and efficient feature selection
(2012-12)
Article
Accés restringit per política de l'editorialA general framework for microarray data classification is proposed in this paper. It pro- duces precise and reliable classifiers through a two-step approach. At first, the original feature set is enhanced by a new set ... -
Hierarchical clustering combining numerical and biological similarities for gene expression data classification
(Institute of Electrical and Electronics Engineers (IEEE), 2013)
Text en actes de congrés
Accés restringit per política de l'editorialHigh throughput data analysis is a challenging problem due to the vast amount of available data. A major concern is to develop algorithms that provide accurate numerical predictions and biologically relevant results. A ... -
Hierarchical information representation and efficient classification of gene expression microarray data
(Universitat Politècnica de Catalunya, 2014-06-27)
Tesi
Accés obertIn the field of computational biology, microarryas are used to measure the activity of thousands of genes at once and create a global picture of cellular function. Microarrays allow scientists to analyze expression of many ... -
Microarray classification with hierarchical data representation and novel feature selection criteria
(Institute of Electrical and Electronics Engineers (IEEE), 2012)
Text en actes de congrés
Accés restringit per política de l'editorialMicroarray data classification is a challenging prob- lem due to the high number of variables compared to the small number of available samples. An effective methodology to output a precise and reliable classifier is ... -
Multiclass cancer-microarray classification algorithm with Pair-Against-All redundancy
(2012)
Text en actes de congrés
Accés restringit per política de l'editorialMulticlass cancer classification is still a challenging task in the field of machine learning. A novel multiclass approach is proposed in this work as a combination of multiple binary classifiers. It is an example of Error ... -
Pan-cancer analysis of whole genomes
(Nature Research, 2020)
Article
Accés obertCancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1,2,3. Here we report the integrative analysis of 2,658 ... -
Predicción de mortalidad en recién nacidos prematuros. Revisión sistemática actualizada
(Elsevier, 2020-07)
Article
Accés obertIntroducción La prematuridad extrema se asocia a altas tasas de mortalidad. Para profesionales y familias, es prioritario establecer de forma individualizada las probabilidades de muerte en diferentes momentos. El objetivo ... -
Prediction of mortality in very low birth weight neonates in Spain
(Public Library of Science, 2020-07)
Article
Accés obertObjective Predictive models for preterm infant mortality have been developed internationally, albeit not valid for all populations. This study aimed to develop and validate different mortality predictive models, using ... -
Rare disease research workflow using multilayer networks elucidates the molecular determinants of severity in Congenital Myasthenic Syndromes
(Nature Research, 2024)
Article
Accés obertExploring the molecular basis of disease severity in rare disease scenarios is a challenging task provided the limitations on data availability. Causative genes have been described for Congenital Myasthenic Syndromes (CMS), ... -
The landscape of expression and alternative splicing variation across human traits
(Elsevier, 2023-01-11)
Article
Accés obertUnderstanding the consequences of individual transcriptome variation is fundamental to deciphering human biology and disease. We implement a statistical framework to quantify the contributions of 21 individual traits as ... -
Tracking of antibiotic resistance transfer and rapid plasmid evolution in a hospital setting by Nanopore sequencing
(American Society for Microbiology, 2020)
Article
Accés obertInfections with multidrug-resistant bacteria often leave limited or no treatment options. The transfer of antimicrobial resistance genes (ARG) carrying plasmids between bacterial species by horizontal gene transfer represents ...
