A5040100241- Gene expression and cancer classification
- Molecular Biology Techniques and Applications
- Context-Aware Activity Recognition Systems
- Anomaly Detection Techniques and Applications
- Machine Learning in Bioinformatics
- Genomics and Phylogenetic Studies
- Bioinformatics and Genomic Networks
- Time Series Analysis and Forecasting
- Cutaneous Melanoma Detection and Management
- Non-Invasive Vital Sign Monitoring
- Radiomics and Machine Learning in Medical Imaging
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Healthcare Technology and Patient Monitoring
- Cancer-related molecular mechanisms research
- Genetics, Bioinformatics, and Biomedical Research
- Skin Protection and Aging
- Digital Imaging for Blood Diseases
- RNA modifications and cancer
- Medical Image Segmentation Techniques
Universidad de Granada
2014-2022
Universidad de La Laguna
1993
Signal segmentation is a crucial stage in the activity recognition process; however, this has been rarely and vaguely characterized so far. Windowing approaches are normally used for segmentation, but no clear consensus exists on which window size should be preferably employed. In fact, most designs rely figures previous works, with strict studies that support them. Intuitively, decreasing allows faster detection, as well reduced resources energy needs. On contrary, large data windows...
Nowadays, many public repositories containing large microarray gene expression datasets are available. However, the problem lies in fact that technology less powerful and accurate than more recent Next Generation Sequencing technologies, such as RNA-Seq. In any case, information from microarrays is truthful robust, thus it can be exploited through integration of data with RNA-Seq data. Additionally, extraction acquisition number samples still entails very high costs terms time computational...
In more recent years, a significant increase in the number of available biological experiments has taken place due to widespread use massive sequencing data. Furthermore, continuous developments machine learning and high performance computing areas, are allowing faster efficient analysis processing this type However, information about certain disease is normally different technologies manufacturers, along years around world. Thus, nowadays it paramount importance attain correct integration...
Many clinical studies have revealed the high biological similarities existing among different skin pathological states. These create difficulties in efficient diagnosis of cancer, and encourage to study design new intelligent decision support systems. In this sense, gene expression analysis can help find differentially expressed genes (DEGs) simultaneously discerning multiple states a single test. The integration heterogeneous transcriptomic datasets requires pipeline stages be properly...
KnowSeq R/Bioc package is designed as a powerful, scalable and modular software focused on automatizing assembling renowned bioinformatic tools with new features functionalities. It comprises unified environment to perform complex gene expression analyses, covering all the needed processing steps identify signature for specific disease gather understandable knowledge. This process may be initiated from raw files either available at well-known platforms or provided by users themselves, in...
Most of the research studies developed applying microarray technology to characterization different pathological states any disease may fail in reaching statistically significant results. This is largely due small repertoire analysed samples, and limitation number or pathologies usually addressed. Moreover, influence potential deviations on gene expression quantification disregarded. In spite continuous changes omic sciences, reflected for instance emergence new Next-Generation...
Background: Despite all the medical advances introduced for personalized patient treatment and research supported in search of genetic patterns inherent to occurrence its different manifestations on human being, unequivocal effective cancer, unfortunately, remains as an unresolved challenge within scientific panorama. Until a universal solution control is achieved, early detection mechanisms preventative diagnosis increasingly avoid treatments, resulting unreliable effectiveness. The...
Abstract The number of gene expression analyses has grown exponentially over the last years. main triggers this increase are reduction in sequencing cost per sample and technological advances, specially computing scope. Those generally involve a steps. Firstly, raw samples alignment quality analysis needed. After that, Differentially Expressed Genes (DEGs) extraction subsequent enrichment can be performed. development intelligent predictive tools results essential bioinformatics given that...
Background: Nowadays, gene expression analysis is one of the most promising pillars for understanding and uncovering mechanisms underlying development spread cancer. In this sense, Next Generation Sequencing technologies, such as RNA-Seq, are currently leading market due to their precision cost. Nevertheless, there still an enormous amount non-analyzed data obtained from older Microarray, which could be useful extract relevant knowledge. Methods: Throughout research, a complete machine...