Browsing GI-RNASA - Artigos by Title
Now showing items 129-148 of 166
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Parallel computing for brain simulation
(Bentham Science, 2017-05-01)[Abstract] Background: The human brain is the most complex system in the known universe, it is therefore one of the greatest mysteries. It provides human beings with extraordinary abilities. However, until now it has not ... -
Perturbation theory/machine learning model of ChEMBL data for dopamine targets: docking, synthesis, and assay of new l-prolyl-l-leucyl-glycinamide peptidomimetics
(American Chemical Society, 2018-05-23)[Abstract] Predicting drug–protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning ... -
Perturbation-Theory Machine Learning (PTML) Multilabel Model of the ChEMBL Dataset of Preclinical Assays for Antisarcoma Compounds
(American Chemical Society, 2020-10-14)[Abstract] Sarcomas are a group of malignant neoplasms of connective tissue with a different etiology than carcinomas. The efforts to discover new drugs with antisarcoma activity have generated large datasets of multiple ... -
Pool-Type FishDesign for a Potamodromous Cyprinid in the Iberian Peninsula: The Iberian Barbel—Synthesis and Future Directions
(M D P I AG, 2020-04-21)[Abstract] The Iberian barbel (Luciobarbus bocagei) is one of the most common cyprinids in the Iberian Peninsula, whose migratory routes are often hampered by anthropogenic barriers. Fishways might be an effective mitigation ... -
Population Subset Selection for the Use of a Validation Dataset for Overfitting Control in Genetic Programming
(Taylor & Francis Group, 2019-07-31)[Abstract] Genetic Programming (GP) is a technique which is able to solve different problems through the evolution of mathematical expressions. However, in order to be applied, its tendency to overfit the data is one of ... -
Praxis dese la teoría, ¿es posible la transferencia desde la universidad a la realidad?
(Asociación Profesional Gallega de Terapia Ocupacional, 2015-10)[Resumen] La praxis, entendida como la aplicación de los propios conocimientos teóricos en la práctica, implica una adecuada conceptualización previa y una completa formación en todas las dimensiones filosóficas ... -
Predicting vertical urban growth using genetic evolutionary algorithms in Tokyo’s minato ward
(American Society of Civil Engineers, 2017-11-28)[Abstract] This article explores the use of evolutionary genetic algorithms to predict scenarios of urban vertical growth in large urban centers. Tokyo’s Minato Ward is used as a case study because it has been one of the ... -
Prediction of Anti-Glioblastoma Drug-Decorated Nanoparticle Delivery Systems Using Molecular Descriptors and Machine Learning
(MDPI, 2021)[Abstract] The theoretical prediction of drug-decorated nanoparticles (DDNPs) has become a very important task in medical applications. For the current paper, Perturbation Theory Machine Learning (PTML) models were built ... -
Prediction of Breast Cancer Proteins Involved in Immunotherapy, Metastasis, and RNA-Binding Using Molecular Descriptors and Artifcial Neural Networks
(Springer Nature, 2020-05-22)[Abstract] Breast cancer (BC) is a heterogeneous disease where genomic alterations, protein expression deregulation, signaling pathway alterations, hormone disruption, ethnicity and environmental determinants are involved. ... -
Prediction of high anti-angiogenic activity peptides in silico using a generalized linear model and feature selection
(Nature, 2018-10-24)[Abstract] Screening and in silico modeling are critical activities for the reduction of experimental costs. They also speed up research notably and strengthen the theoretical framework, thus allowing researchers to ... -
Prediction of Nucleoitide Binding Peptides Using Star Graph Topological Índices
(Elsevier, 2015-08-05)[Abstract] The nucleotide binding proteins are involved in many important cellular processes, such as transmission of genetic information or energy transfer and storage. Therefore, the screening of new peptides for this ... -
Random Forest Classification Based on Star Graph Topological Indices for Antioxidant Proteins
(Elsevier, 2012-10-29)[Abstract] Aging and life quality is an important research topic nowadays in areas such as life sciences, chemistry, pharmacology, etc. People live longer, and, thus, they want to spend that extra time with a better quality ... -
Random Forest-Based Prediction of Stroke Outcome
(Nature Research, 2021)[Abstract] We research into the clinical, biochemical and neuroimaging factors associated with the outcome of stroke patients to generate a predictive model using machine learning techniques for prediction of mortality and ... -
S2SNet: a tool for transforming characters and numeric sequences into star network topological indices in chemoinformatics, bioinformatics, biomedical, and social-legal sciences
(Bentham, 2013)[Abstract] The study of complex systems such as proteins/DNA/RNA or dynamics of tax law systems can be carried out with the complex network theory. This allows the numerical quantification of the significant information ... -
Self-tuning of disk input–output in operating systems
(Elsevier Inc., 2012-01)One of the most difficult and hard to learn tasks in computer system management is tuning the kernel parameters in order to get the maximum performance. Traditionally, this tuning has been set using either fixed configurations ... -
SNOMED2HL7: a tool to normalize and bind SNOMED CT concepts to the HL7 Reference Information Model
(Elsevier, 2017-10)[Abstract] BACKGROUND: Current clinical research and practice requires interoperability among systems in a complex and highly dynamic domain. There has been a significant effort in recent years to develop integrative common ... -
SNP locator: a candidate SNP selection tool
(Inderscience, 2013)[Abstract] In this work, a data integration approach using a federated model based on a service oriented architecture (SOA) is presented. The BioMOBY middleware was used to implement each service which is part of the ... -
Special Issue on Applied Artificial Neural Networks
(Multidisciplinary Digital Publishing Institute (MDPI), 2022)[Abstract]: Over the years there have been many attempts to understand, and subsequently imitate, the way that humans try to solve problems, so it can help to artificially achieve the same kind of intelligent behavior. ... -
State of the Art on Artificial Intelligence in Land Use Simulation
(Hindawi Limited, 2022)[Abstract] This review presents a state of the art in artificial intelligence applied to urban planning and particularly to land-use predictions. In this review, different articles after the year 2016 are analyzed mostly ... -
Study of classical conditioning in Aplysia through the implementation of computational models of its learning circuit
(Taylor & Francis, 2007-07-04)The learning phenomenon can be analysed at various levels, but in this paper we treat a specific paradigm of artificial intelligence, i.e. artificial neural networks (ANNs), whose main virtue is their capacity to ...
