Argitalpenak (22) DANIEL CASTILLO SECILLA argitalpenak

2024

  1. Improving the Performance of EA-based Multi-population Models for Feature Selection Problems by Reducing the Individual Size in the Initial Population

    GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion

2023

  1. Boosting NSGA-II-Based Wrappers Speedup for High-Dimensional Data: Application to EEG Classification

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Comprehensive Pan-cancer Gene Signature Assessment through the Implementation of a Cascade Machine Learning System

    Current Bioinformatics, Vol. 18, Núm. 1, pp. 40-54

  3. Novel Gene Signature for Bladder Cancer Stage Identification

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  4. Predicting COVID-19 Severity Integrating RNA-Seq Data Using Machine Learning Techniques

    Current Bioinformatics, Vol. 18, Núm. 3, pp. 221-231

  5. Towards the Identification of Multiclass Lung Cancer-Related Genes: An Evolutionary and Intelligent Procedure

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2022

  1. COVID-19 Biomarkers Recognition & Classification Using Intelligent Systems

    Current Bioinformatics, Vol. 17, Núm. 5, pp. 426-439

  2. Gene Expression Tools from a Technical Perspective: Current Approaches and Alternative Solutions for the KnowSeq Suite

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. Heterogeneous Gene Expression Cross-evaluation of Robust Biomarkers Using Machine Learning Techniques Applied to Lung Cancer

    Current Bioinformatics, Vol. 17, Núm. 2, pp. 150-163

  4. Machine-Learning-Based Late Fusion on Multi-Omics and Multi-Scale Data for Non-Small-Cell Lung Cancer Diagnosis

    Journal of Personalized Medicine, Vol. 12, Núm. 4

2021

  1. COVID-19 Biomarkers Detection Using ‘KnowSeq’ R Package

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Comparison of Fusion Methodologies Using CNV and RNA-Seq for Cancer Classification: A Case Study on Non-Small-Cell Lung Cancer

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. KnowSeq R-Bioc package: The automatic smart gene expression tool for retrieving relevant biological knowledge

    Computers in Biology and Medicine, Vol. 133

  4. Non-small-cell lung cancer classification via RNA-Seq and histology imaging probability fusion

    BMC Bioinformatics, Vol. 22, Núm. 1

  5. Preface

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2020

  1. Enhancing Breast Cancer Classification via Information and Multi-model Integration

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Towards Improving Skin Cancer Diagnosis by Integrating Microarray and RNA-Seq Datasets

    IEEE Journal of Biomedical and Health Informatics, Vol. 24, Núm. 7, pp. 2119-2130

2019

  1. Feature Selection and Assessment of Lung Cancer Sub-types by Applying Predictive Models

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Leukemia multiclass assessment and classification from Microarray and RNA-seq technologies integration at gene expression level

    PLoS ONE, Vol. 14, Núm. 2

2018

  1. Multiclass classification for skin cancer profiling based on the integration of heterogeneous gene expression series

    PLoS ONE, Vol. 13, Núm. 5