Browsing by author "López Fernández, Hugo"

Application of data mining and artificial intelligence techniques to mass spectrometry data for knowledege discovery

doctoralThesis
Informática
Programa Oficial de Doutoramento en Sistemas Software Intelixentes e Adaptables (RD 1393/2007)

ATXN1 N-terminal region explains the binding differences of wild-type and expanded forms

Rocha, Sara; Vieira, Jorge; Vázquez González, Noé; López Fernández, Hugo

; Fernández Riverola, Florentino

; Reboiro Jato, Miguel

; Sousa, André D.; Vieira, Cristina P.
article
Informática

Compi: a framework for portable and reproducible pipelines

López Fernández, Hugo

; Graña Castro, Osvaldo; Nogueira Rodríguez, Alba

; Reboiro Jato, Miguel

; González Peña, Daniel

article
Informática

Deep learning techniques for computer-aided diagnosis in colorectal cancer

Nogueira Rodríguez, Alba

doctoralThesis
Informática
Programa de Doutoramento en Sistemas de Software Intelixentes e Adaptables (RD 99/2011)

Deep neural networks approaches for detecting and classifying colorectal polyps

Nogueira Rodríguez, Alba

; Domínguez Carbajales, Rubén; López Fernández, Hugo

; Iglesias, Águeda; Cubiella Fernández, Joaquín; Fernández Riverola, Florentino

; Reboiro Jato, Miguel

; González Peña, Daniel

article
Informática

GC4S: A bioinformatics-oriented Java software library of reusable graphical user interface components

López Fernández, Hugo

; Reboiro Jato, Miguel

; González Peña, Daniel

; Laza Fidalgo, Rosalía

; Pavón Rial, Maria Reyes

; Fernández Riverola, Florentino

article
Informática

Large scale analyses and visualization of adaptive amino acid changes projects

Vázquez González, Noé; Vieira, Cristina P; Amorim, Bárbara S. R; Torres Plasencia, Gustavo André

; López Fernández, Hugo

; Fernández Riverola, Florentino

; Sousa, José L. R; Reboiro Jato, Miguel

; Vieira, Jorge
article
Informática

Multiple independent L-gulonolactone oxidase (GULO) gene losses and vitamin C synthesis reacquisition events in non-Deuterostomian animal species

Henriques, Sílvia F.; Duque, Pedro; López Fernández, Hugo

; Vázquez, Noé; Fernández Riverola, Florentino

; Reboiro Jato, Miguel

; Vieira, Cristina P.; Vieira, Jorge
article
Informática

MyBrain-Seq: a pipeline for MiRNA-seq data analysis in neuropsychiatric disorders

Pérez Rodríguez, Daniel; Agis Balboa, Roberto Carlos; López Fernández, Hugo

article
Informática

Negative samples for improving object detection—A case study in aI-assisted colonoscopy for polyp detection

Nogueira Rodríguez, Alba

; González Peña, Daniel

; Reboiro Jato, Miguel

; López Fernández, Hugo

article
Informática

Performance of convolutional neural networks for polyp localization on public colonoscopy image datasets

Nogueira Rodríguez, Alba

; Reboiro Jato, Miguel

; González Peña, Daniel

; López Fernández, Hugo

article
Informática

Real-time polyp detection model using convolutional neural networks

Nogueira Rodriguez, Alba; Domínguez Carbajales, Rubén; Campos Tato, Fernando; Herrero, Jesús; Puga, Manuel; Remedios, David; Rivas, Laura; Sánchez, Eloy; Iglesias, Águeda; Cubiella Fernández, Joaquín; Fernández Riverola, Florentino

; López Fernández, Hugo

; Reboiro Jato, Miguel

; González Peña, Daniel

article
Informática

An RNA-seq based machine learning approach identifies latent tuberculosis patients with an active tuberculosis profile

Estévez Martínez, Olivia

; Anibarro García, Luis; Garet, Elina; Pallares, Ángeles; Barcia, Laura; Calviño, Laura; Maueia, Cremildo; Mussá, Tufária; Fernández Riverola, Florentino

; González Peña, Daniel

; Reboiro Jato, Miguel

; López Fernández, Hugo

; Fonseca, Nuno A.; Reljic, Rajko; González Fernández, Maria Africa

article
Dpto. Externo

Browsing by author "López Fernández, Hugo"

Application of data mining and artificial intelligence techniques to mass spectrometry data for knowledege discovery ﻿

ATXN1 N-terminal region explains the binding differences of wild-type and expanded forms ﻿

Compi: a framework for portable and reproducible pipelines ﻿

Deep learning techniques for computer-aided diagnosis in colorectal cancer ﻿

Deep neural networks approaches for detecting and classifying colorectal polyps ﻿

GC4S: A bioinformatics-oriented Java software library of reusable graphical user interface components ﻿

Large scale analyses and visualization of adaptive amino acid changes projects ﻿

Multiple independent L-gulonolactone oxidase (GULO) gene losses and vitamin C synthesis reacquisition events in non-Deuterostomian animal species ﻿

MyBrain-Seq: a pipeline for MiRNA-seq data analysis in neuropsychiatric disorders ﻿

Negative samples for improving object detection—A case study in aI-assisted colonoscopy for polyp detection ﻿

Performance of convolutional neural networks for polyp localization on public colonoscopy image datasets ﻿

Real-time polyp detection model using convolutional neural networks ﻿

An RNA-seq based machine learning approach identifies latent tuberculosis patients with an active tuberculosis profile ﻿

El Repositorio Institucional de la Universidade de Vigo Investigo se difunde en:

Application of data mining and artificial intelligence techniques to mass spectrometry data for knowledege discovery

ATXN1 N-terminal region explains the binding differences of wild-type and expanded forms

Compi: a framework for portable and reproducible pipelines

Deep learning techniques for computer-aided diagnosis in colorectal cancer

Deep neural networks approaches for detecting and classifying colorectal polyps

GC4S: A bioinformatics-oriented Java software library of reusable graphical user interface components

Large scale analyses and visualization of adaptive amino acid changes projects

Multiple independent L-gulonolactone oxidase (GULO) gene losses and vitamin C synthesis reacquisition events in non-Deuterostomian animal species

MyBrain-Seq: a pipeline for MiRNA-seq data analysis in neuropsychiatric disorders

Negative samples for improving object detection—A case study in aI-assisted colonoscopy for polyp detection

Performance of convolutional neural networks for polyp localization on public colonoscopy image datasets

Real-time polyp detection model using convolutional neural networks

An RNA-seq based machine learning approach identifies latent tuberculosis patients with an active tuberculosis profile