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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 ...
Integrative Multi-Omics Data-Driven Approach for Metastasis Prediction in Cancer
(ACM, 2018)
[Abstract]
Nowadays biomedical research is generating huge amounts of omic data, covering all levels of genetic information from nucleotide sequencing to protein metabolism. In the beginning, data were analyzed independently ...
Texture Analysis in Gel Electrophoresis Images Using an Integrative Kernel-Based Approach
(Nature, 2016-01-13)
[Abstract] Texture information could be used in proteomics to improve the quality of the image analysis of proteins separated on a gel. In order to evaluate the best technique to identify relevant textures, we use several ...
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 ...
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. ...
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 ...
Texture classification of proteins using support vector machines and bio-inspired metaheuristics
(Springer, 2014-11-02)
[Abstract] In this paper, a novel classification method of two-dimensional polyacrylamide gel electrophoresis images is presented. Such a method uses textural features obtained by means of a feature selection process for ...
Machine Learning Techniques for Single Nucleotide Polymorphism—Disease Classification Models in Schizophrenia
(Molecular Diversity Preservation International, 2010)
[Abstract] Single nucleotide polymorphisms (SNPs) can be used as inputs in disease computational studies such as pattern searching and classification models. Schizophrenia is an example of a complex disease with an important ...
Improvement of Epitope Prediction Using Peptide Sequence Descriptors and Machine Learning
(MDPI, 2019)
[Abstract] In this work, we improved a previous model used for the prediction of proteomes as new
B-cell epitopes in vaccine design. The predicted epitope activity of a queried peptide is based on its
sequence, a known ...
Developing a Secure Low-Cost Radon Monitoring System
(MDPI AG, 2020-01-29)
[Abstract] Radon gas has been declared a human carcinogen by the United States Environmental Protection Agency (USEPA) and the International Agency for Research on Cancer (IARC). Several studies carried out in Spain ...
