25 Result(s)
within
Juan Luis Fernández-Martínez
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Article
Leveraging GWAS data derived from a large cooperative group trial to assess the risk of taxane-induced peripheral neuropathy (TIPN) in patients being treated for breast cancer: Part 2—functional implications of a SNP cluster associated with TIPN risk in patients being treated for breast cancer
Using GWAS data derived from a large collaborative trial (ECOG-5103), we identified a cluster of 267 SNPs which predicted CIPN in treatment-naive patients as reported in Part 1 of this study. To assess the fun...
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Article
Identification of a SNP cluster associated with taxane-induced peripheral neuropathy risk in patients being treated for breast cancer using GWAS data derived from a large cooperative group trial
Chemotherapy-induced peripheral neuropathy (CIPN) is a common toxicity of taxanes for which there is no effective intervention. Genomic CIPN risk determination has yielded promising, but inconsistent results....
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Chapter and Conference Paper
Computational Models for COVID-19 Dynamics Prediction
In a viral pandemic, predicting the number of infected per day and the total number of cases in each wave of possible variants is intended to aid decision-making in real public health practice. This paper comp...
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Chapter and Conference Paper
Prediction of Functional Effects of Protein Amino Acid Mutations
Human Single Amino Acid Polymorphisms (SAPs) or Single Amino Acid Variants (SAVs) usually named as nonsynonymous Single Nucleotide Variants nsSNVs) represent the most frequent type of genetic variation among t...
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Chapter
The PSO Family: Application to the Portfolio Optimization Problem
Nonlinear high-dimensional optimization problems are generally ill-posed and ill-conditioned, with different sets of models located in one or different disconnected valleys of the cost function landscape with ...
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Chapter
Self-potential Inversion and Uncertainty Analysis via the Particle Swarm Optimization (PSO) Family
Water flow in the subsoil and pum** tests generate electrical currents measurable at the ground surface and terms spontaneous potential (SP) anomalies that are well correlated with the geometry of the water ...
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Article
Open AccessRobust pathway sampling in phenotype prediction. Application to triple negative breast cancer
Phenotype prediction problems are usually considered ill-posed, as the amount of samples is very limited with respect to the scrutinized genetic probes. This fact complicates the sampling of the defective gene...
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Chapter and Conference Paper
The Utilization of Different Classifiers to Perform Drug Repositioning in Inclusion Body Myositis Supports the Concept of Biological Invariance
In this research work, we introduce several novel methods to identify the defective pathways in highly uncertain phenotype prediction problems. More specifically, we applied these methodologies for phenotype p...
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Article
Predicting protein tertiary structure and its uncertainty analysis via particle swarm sampling
We discuss the relationship between the problem of protein tertiary structure prediction from the amino acid sequence and the uncertainty analysis. The algorithm presented in this paper belongs to the category...
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Chapter and Conference Paper
Detection of Breast Cancer Using Infrared Thermography and Deep Neural Networks
We present a preliminary analysis about the use of convolutional neural networks (CNNs) for the early detection of breast cancer via infrared thermography. The two main challenges of using CNNs are having at ...
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Article
Open AccessmGluR5 mediates post-radiotherapy fatigue development in cancer patients
Cancer-related fatigue (CRF) is a common burden in cancer patients and little is known about its underlying mechanism. The primary aim of this study was to identify gene signatures predictive of post-radiother...
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Chapter and Conference Paper
On the Use of Principal Component Analysis and Particle Swarm Optimization in Protein Tertiary Structure Prediction
We discuss applicability of Principal Component Analysis and Particle Swarm Optimization in protein tertiary structure prediction. The proposed algorithm is based on establishing a low-dimensional space where ...
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Chapter and Conference Paper
Sampling Defective Pathways in Phenotype Prediction Problems via the Holdout Sampler
In this paper, we introduce the holdout sampler to find the defective pathways in high underdetermined phenotype prediction problems. This sampling algorithm is inspired by the bootstrap** procedure used in ...
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Chapter and Conference Paper
Sampling Defective Pathways in Phenotype Prediction Problems via the Fisher’s Ratio Sampler
In this paper, we introduce the Fisher’s ratio sampler that serves to unravel the defective pathways in highly underdetermined phenotype prediction problems. This sampling algorithm first selects the most disc...
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Chapter and Conference Paper
Protein Tertiary Structure Prediction via SVD and PSO Sampling
We discuss the use of the Singular Value Decomposition as a model reduction technique in Protein Tertiary Structure prediction, alongside to the uncertainty analysis associated to the tertiary protein predicti...
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Chapter and Conference Paper
Comparison of Different Sampling Algorithms for Phenotype Prediction
In this paper, we compare different sampling algorithms used for identifying the defective pathways in highly underdetermined phenotype prediction problems. The first algorithm (Fisher’s ratio sampler) selects...
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Chapter
Improvements in Resampling Techniques for Phenotype Prediction: Applications to Neurodegenerative Diseases
Searching for new biomarkers, biological networks and pathways is crucial in the solution of neurodegenerative diseases. In this research we have compared three different algorithms and resampling techniques t...
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Article
Erratum to: Assessing concrete strength with rebound hammer: review of key issues and ideas for more reliable conclusions
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Chapter and Conference Paper
Aligned PSO for Optimization of Image Processing Methods Applied to the Face Recognition Problem
This paper is devoted to present the stochastic stability analysis of a novel PSO version, the aligned PSO, and its application to the face recognition problem using supervised learning techniques. Its applica...
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Chapter and Conference Paper
Particle Swarm Optimization: A Powerful Family of Stochastic Optimizers. Analysis, Design and Application to Inverse Modelling
Inverse problems are ill-posed: the error function has its minimum in a flat elongated valley or surrounded by many local minima. Local optimization methods give unpredictable results if no prior information i...
