A5023055680- Gene expression and cancer classification
- Ferroptosis and cancer prognosis
- MicroRNA in disease regulation
- Statistical Distribution Estimation and Applications
- Bioinformatics and Genomic Networks
- Advanced Statistical Methods and Models
- Metabolomics and Mass Spectrometry Studies
- Advanced Proteomics Techniques and Applications
- Bayesian Modeling and Causal Inference
- Cancer, Hypoxia, and Metabolism
- Bladder and Urothelial Cancer Treatments
- Probabilistic and Robust Engineering Design
- Molecular Biology Techniques and Applications
- Cancer, Lipids, and Metabolism
- RNA modifications and cancer
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Computational Drug Discovery Methods
- Cancer Cells and Metastasis
- Diet and metabolism studies
- Microbial Metabolic Engineering and Bioproduction
- Bayesian Methods and Mixture Models
- Cancer Immunotherapy and Biomarkers
- Financial Risk and Volatility Modeling
- AI-based Problem Solving and Planning
National University of Distance Education
2012-2023
Distance State University
2018
Universidad Complutense de Madrid
2013
Research Institute Hospital 12 de Octubre
2013
RTI International
1999
Abstract Triple-negative breast cancer is a heterogeneous disease characterized by lack of hormonal receptors and HER2 overexpression. It the only subgroup that does not benefit from targeted therapies, its prognosis poor. Several studies have developed specific molecular classifications for triple-negative cancer. However, these subtypes had little impact in clinical setting. Gene expression data information 494 tumors were obtained public databases. First, probabilistic graphical model...
Better knowledge of the biology breast cancer has allowed use new targeted therapies, leading to improved outcome. High-throughput technologies allow deepening into molecular architecture cancer, integrating different levels information, which is important if it helps in making clinical decisions. microRNA (miRNA) and protein expression profiles were obtained from 71 estrogen receptor-positive (ER(+)) 25 triple-negative (TNBC) samples. RNA proteins formalin-fixed, paraffin-embedded tumors...
Abstract Breast cancer is a heterogeneous disease comprising variety of entities with various genetic backgrounds. Estrogen receptor-positive, human epidermal growth factor receptor 2-negative tumors typically have favorable outcome; however, some patients eventually relapse, which suggests heterogeneity within this category. In the present study, we used proteomics and miRNA profiling techniques to characterize set 102 either estrogen receptor-positive (ER+)/progesterone (PR+) or...
Abstract
Metabolic reprogramming is a hallmark of cancer. It has been described that breast cancer subtypes present metabolism differences and this fact enables the possibility using metabolic inhibitors as targeted drugs in specific scenarios. In study, cell lines were treated with metformin rapamycin, showing heterogeneous response to treatment leading cycle disruption. The genetic causes molecular effects differential characterized by means SNP genotyping mass spectrometry-based proteomics....
Traditionally, bladder cancer has been classified based on histology features. Recently, some works have proposed a molecular classification of invasive tumors. To determine whether proteomics can define subtypes muscle urothelial (MIUC) and allow evaluating the status biological processes its clinical value. 58 MIUC patients who underwent curative surgical resection at our institution between 2006 2012 were included. Proteome was evaluated by high-throughput in routinely archive FFPE tumor...
Muscle-invasive bladder tumors are associated with a high risk of relapse and metastasis even after neoadjuvant chemotherapy radical cystectomy. Therefore, further therapeutic options needed molecular characterization the disease may help to identify new targets. The aim this study was characterize muscle-invasive at level using computational analyses. TCGA cohort cancer patients used describe these tumors. Probabilistic graphical models, layer analyses based on sparse k-means coupled...
Abstract Background Metabolomics has a great potential in the development of new biomarkers cancer and it experiment recent technical advances. Methods In this study, metabolomics gene expression data from 67 localized (stage I to IIIB) breast tumor samples were analyzed, using (1) probabilistic graphical models define associations quantitative without other priori information; (2) Flux Balance Analysis flux activities characterize differences metabolic pathways. Results On one hand, both...
One of the drawbacks we face up when analyzing gene to phenotype associations in genomic data is ugly performance designed classifier due small sample-high dimensional structures (n ≪ p) at hand. This known as peaking phenomenon, a common situation analysis expression data. Highly predictive bivariate interactions whose marginals are useless for discrimination also affected by such so they commonly discarded state art sequential search algorithms. Such patterns weak/marginal strong...
Breast cancer is the most frequent tumor in women and its incidence increasing. Neoadjuvant chemotherapy has become standard of care as a complement to surgery locally advanced or poor-prognosis early stage disease. The achievement complete response neoadjuvant correlates with prognosis but it not possible predict who will obtain an excellent response. molecular analysis offers unique opportunity unveil predictive factors. In this work, gene expression profiling 279 samples from patients...
Non-normality is a usual fact when dealing with gene expression data. Thus, flexible models are needed in order to account for the underlying asymmetry and heavy tails of multivariate measures. This paper addresses issue by exploring projection pursuit problem under framework where model assumed follow skew-t distribution. Under this assumption, skewness kurtosis indices addressed as natural approach data reduction. The work examines its properties giving some theoretical insights delving...
Breast cancer is a heterogeneous disease. In clinical practice, tumors are classified as hormonal receptor positive, Her2 positive and triple negative tumors. previous works, our group defined new subgroup, the TN-like subtype, which had prognosis molecular profile more similar to this study, proteomics Bayesian networks were used characterize protein relationships in 96 breast tumor samples. Components obtained by these methods clear functional structure. The analysis of components...
ABSTRACT The multivariate exponential power is a useful distribution for modeling departures from normality in data by means of tail weight scalar parameter that regulates the non-normality model. incorporation shape asymmetry vector into model serves to account potential asymmetries and gives rise skew distribution. This work aimed at revisiting taking as starting point its formulation scale mixture skew-normal distributions. paper provides some highlights theoretical insights on role...