Browsing GI-RNASA - Artigos by Title
Now showing items 31-50 of 164
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Bio-AIMS collection of chemoinformatics web tools based on molecular graph information and artificial intelligence models
(Bentham, 2015-09-01)[Abstract] The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction ... -
Biomedical data integration in computational drug design and bioinformatics
(Bentham Science, 2013)[Abstract In recent years, in the post genomic era, more and more data is being generated by biological high throughput technologies, such as proteomics and transcriptomics. This omics data can be very useful, but the real ... -
BiOSS: A system for biomedical ontology selection
(Elsevier Ireland Ltd, 2014-04)In biomedical informatics, ontologies are considered a key technology for annotating, retrieving and sharing the huge volume of publicly available data. Due to the increasing amount, complexity and variety of existing ... -
Breast density classification to reduce false positives in CADe systems
(Elsevier, 2013)[Abstract] This paper describes a novel weighted voting tree classification scheme for breast density classification. Breast parenchymal density is an important risk factor in breast cancer. Moreover, it is known that ... -
Carbapenem Resistance in Acinetobacter nosocomialis and Acinetobacter junii Conferred by Acquisition of blaOXA-24/40 and Genetic Characterization of the Transmission Mechanism between Acinetobacter Genomic Species
(American Society for Microbiology, 2022)[Abstract] Carbapenem resistance is increasing among Gram-negative bacteria, including the genus Acinetobacter. This study aimed to characterize, for the first time, the development of carbapenem resistance in clinical ... -
Carbon nanotubes’ effect on mitochondrial oxygen flux dynamics: polarography experimental study and machine learning models using star graph trace invariants of Raman spectra
(MDPI, 2017-11-11)[Abstract] This study presents the impact of carbon nanotubes (CNTs) on mitochondrial oxygen mass flux (Jm) under three experimental conditions. New experimental results and a new methodology are reported for the first ... -
Carbon Nanotubes’ Effect on Mitochondrial Oxygen Flux Dynamics: Polarography Experimental Study and Machine Learning Models using Star Graph Trace Invariants of Raman Spectra
(M D P I AG, 2017-11-11)[Abstract] This study presents the impact of carbon nanotubes (CNTs) on mitochondrial oxygen mass flux (Jm) under three experimental conditions. New experimental results and a new methodology are reported for the first ... -
Classical Music Prediction and Composition by Means of Variational Autoencoders
(MDPI AG, 2020-04-27)[Abstract] This paper proposes a new model for music prediction based on Variational Autoencoders (VAEs). In this work, VAEs are used in a novel way to address two different issues: music representation into the latent ... -
Classification of mild cognitive impairment and Alzheimer’s Disease with machine-learning techniques using 1H Magnetic Resonance Spectroscopy data
(Elsevier, 2015-03-30)[Abstract] Several magnetic resonance techniques have been proposed as non-invasive imaging biomarkers for the evaluation of disease progression and early diagnosis of Alzheimer’s Disease (AD). This work is the first ... -
Classification of Signals by Means of Genetic Programming
(Springer, 2013-03-30)[Abstract] This paper describes a new technique for signal classification by means of Genetic Programming (GP). The novelty of this technique is that no prior knowledge of the signals is needed to extract the features. ... -
Comparativa de metodologías de desarrollo de aplicaciones móviles
(3Ciencias, 2021)[Resumen] El desarrollo de aplicaciones móviles en la actualidad tiene una gran aceptación gracias al avance de la tecnología y producción de toda clase de dispositivos que permiten a los usuarios realizar tareas ... -
Comparison of Outlier-Tolerant Models for Measuring Visual Complexity
(MDPI AG, 2020-04-24)[Abstract] Providing the visual complexity of an image in terms of impact or aesthetic preference can be of great applicability in areas such as psychology or marketing. To this end, certain areas such as Computer Vision ... -
Complex systems in aesthetics and arts
(Hindawi, 2019-05-02) -
Computational models of neuron-astrocyte interactions lead to improved efficacy in the performance of neural networks
(Hindawi, 2012)[Abstract] The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has ... -
Conversations About Self-Identity in Alzheimer Disease: Augmentative and Alternative Communication Memory Books as an Aid
(Elsevier, 2013-09-18)[Abstract] Alzheimer disease (AD) is a progressive and degenerative neurological disorder that affects memory, language and communication, thinking, and social skills. The inability to recall incidents and events, especially ... -
Convolutional Neural Networks for Sleep Stage Scoring on a Two-Channel EEG Signal
(Springer Nature, 2019-06-26)[Abstract] Sleeping problems have become one of the major diseases all over the world. To tackle this issue, the basic tool used by specialists is the Polysomnogram, which is a collection of different signals recorded ... -
Decrypting strong and weak single-walled carbon nanotubes interactions with mitochondrial voltage-dependent anion channels using molecular docking and perturbation theory
(Nature, 2017-10-16)[Abstract] The current molecular docking study provided the Free Energy of Binding (FEB) for the interaction (nanotoxicity) between VDAC mitochondrial channels of three species (VDAC1-Mus musculus, VDAC1-Homo sapiens, ... -
Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications
(MDPI, 2016-08-11)[Abstract] Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other ... -
Detection of Bovine Mastitis in Raw Milk, Using a Low-Cost NIR Spectrometer and k-NN Algorithm
(MDPI, 2021)[Abstract] Among the bovine diseases, mastitis causes high economic losses in the dairy production system. Nowadays, detection under field conditions is mainly performed by the California Mastitis Test, which is considered ... -
Determination of Egg Storage Time at Room Temperature Using a Low-Cost NIR Spectrometer and Machine Learning Techniques
(Elsevier, 2017-12-21)[Abstract] Currently, consumers are more concerned about freshness and quality of food. Poultry egg storage time is a freshness and quality indicator in industrial and consumer applications, even though egg marking is not ...
