• Applied Computational Techniques on Schizophrenia Using Genetic Mutations 

      Aguiar-Pulido, Vanessa; Gestal, M.; Fernández-Lozano, Carlos; Rivero, Daniel; Munteanu, Cristian-Robert (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 ...
    • Biomedical data integration in computational drug design and bioinformatics 

      Seoane, José A.; Aguiar-Pulido, Vanessa; Munteanu, Cristian-Robert; Rivero, Daniel; Rabuñal, Juan R.; Dorado, Julián; Pazos, A. (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 ...
    • Evolutionary Computation and QSAR Research 

      Aguiar-Pulido, Vanessa; Gestal, M.; Cruz-Monteagudo, Maykel; Rabuñal, Juan R.; Dorado, Julián; Munteanu, Cristian-Robert (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 ...
    • Exploring Patterns of Epigenetic Information With Data Mining Techniques 

      Aguiar-Pulido, Vanessa; Seoane, José A.; Gestal, M.; Dorado, Julián (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 ...
    • Graph-based processing of macromolecular information 

      Munteanu, Cristian-Robert; Aguiar-Pulido, Vanessa; Freire, Ana; Martínez-Romero, Marcos; Porto-Pazos, Ana B.; Pereira-Loureiro, Javier; Dorado, Julián (Bentham Science, 2015)
      [Abstract] The complex information encoded into the element connectivity of a system gives rise to the possibility of graphical processing of divisible systems by using the Graph theory. An application in this sense is the ...
    • Machine Learning Techniques for Single Nucleotide Polymorphism—Disease Classification Models in Schizophrenia 

      Aguiar-Pulido, Vanessa; Seoane, José A.; Rabuñal, Juan R.; Dorado, Julián; Pazos, A.; Munteanu, Cristian-Robert (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 ...
    • Random Forest Classification Based on Star Graph Topological Indices for Antioxidant Proteins 

      Fernández-Blanco, Enrique; Aguiar-Pulido, Vanessa; Munteanu, Cristian-Robert; Dorado, Julián (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 ...
    • SNP locator: a candidate SNP selection tool 

      Seoane, José A.; Aguiar-Pulido, Vanessa; Cabarcos, Alba; Quintela, Sonsoles; Rabuñal, Juan R.; Dorado, Julián (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 ...
    • Using Genetic Algorithms for Automatic Recurrent ANN Development: an Application to EEG Signal Classification 

      Rivero, Daniel; Aguiar-Pulido, Vanessa; Fernández-Blanco, Enrique; Gestal, M. (Inderscience, 2013)
      [Abstract] ANNs are one of the most successful learning systems. For this reason, many techniques have been published that allow the obtaining of feed-forward networks. However, fe w ...