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Markov Mean Properties for Cell Death-Related Protein Classification
(Elsevier, 2014-01-31)
[Abstract] The cell death (CD) is a dynamic biological function involved in physiological and pathological processes. Due to the complexity of CD, there is a demand for fast theoretical methods that can help to find new ...
Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection Within Fruit Juice Classification
(Hindawi, 2013-10-21)
[Abstract] Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines ...
Applied Computational Techniques on Schizophrenia Using Genetic Mutations
(Bentham, 2013-03-01)
[Abstract] Schizophrenia is a complex disease, with both genetic and environmental influence. Machine learning techniques can be used to associate different genetic variations at different genes with a (schizophrenic or ...
Mejora continua de la calidad de la docencia a partir del análisis de los resultados de evaluación
(Asociación de Enseñantes Universitarios de la Informática (AENUI), 2018)
[Resumen] El objetivo de cualquier docente debería ser la mejora continua en sus materias. En este trabajo se muestra una aproximación para adecuar las enseñanzas a aquellos aspectos más necesarios dentro de una materia. ...
Kernel-Based Feature Selection Techniques for Transport Proteins Based on Star Graph Topological Indices
(Bentham, 2013)
[Abstract] The transport of the molecules inside cells is a very important topic, especially in Drug Metabolism. The experimental testing of the new proteins for the transporter molecular function is expensive and inefficient ...
Net-Net AutoML Selection of Artificial Neural Network Topology for Brain Connectome Prediction
(MDPI, 2020-02-14)
[Abstract]
Brain Connectome Networks (BCNs) are defined by brain cortex regions (nodes) interacting with others by electrophysiological co-activation (edges). The experimental prediction of new interactions in BCNs ...
Evolutionary Computation and QSAR Research
(Bentham Science, 2013)
[Abstract] The successful high throughput screening of molecule libraries for a specific biological property is one of the main improvements in drug discovery. The virtual molecular filtering and screening relies greatly ...
Using Genetic Algorithms to Improve Support Vector Regression in the Analysis of Atomic Spectra of Lubricant Oils
(Emerald, 2016-06)
[Abstract] Purpose
– The purpose of this paper is to assess the quality of commercial lubricant oils. A spectroscopic method was used in combination with multivariate regression techniques (ordinary multivariate ...
Exploring Patterns of Epigenetic Information With Data Mining Techniques
(Bentham, 2013-02-01)
[Abstract] Data mining, a part of the Knowledge Discovery in Databases process (KDD), is the process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database ...
A methodology for the design of experiments in computational intelligence with multiple regression models
(Peer J, 2016-12-01)
[Abstract] The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the ...