Francisco M. Ortuño Guzman
Orcid: 0000-0001-7424-1753Affiliations:
- University of Granada, Spain
According to our database1,
Francisco M. Ortuño Guzman
authored at least 25 papers
between 2011 and 2023.
Collaborative distances:
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on ugr.es
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Bibliography
2023
Proceedings of the Bioinformatics and Biomedical Engineering, 2023
Uterine Cervix and Corpus Cancers Characterization Through Gene Expression Analysis Using the KnowSeq Tool.
Proceedings of the Bioinformatics and Biomedical Engineering, 2023
2021
A versatile workflow to integrate RNA-seq genomic and transcriptomic data into mechanistic models of signaling pathways.
PLoS Comput. Biol., 2021
Nucleic Acids Res., 2021
KnowSeq R-Bioc package: The automatic smart gene expression tool for retrieving relevant biological knowledge.
Comput. Biol. Medicine, 2021
2020
Towards Improving Skin Cancer Diagnosis by Integrating Microarray and RNA-Seq Datasets.
IEEE J. Biomed. Health Informatics, 2020
2015
Comparing different machine learning and mathematical regression models to evaluate multiple sequence alignments.
Neurocomputing, 2015
Integrative gene expression analysis of lung cancer based on a technology-merging approach.
Proceedings of the IEEE EUROCON 2015, 2015
2014
Case Report: "ADHD Trainer": the mobile application that enhances cognitive skills in ADHD patients.
F1000Research, 2014
Development of Soft-Computing techniques capable of diagnosing Alzheimers Disease in its pre-clinical stage combining MRI and FDG-PET images.
Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering, 2014
Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering, 2014
Creation of a Database Including a Set of Biological Features Related to Protein Sequences and Their Corresponding Alignment.
Proceedings of the 2014 IEEE 27th International Symposium on Computer-Based Medical Systems, 2014
2013
An effective, practical and low computational cost framework for the integration of heterogeneous data to predict functional associations between proteins by means of Artificial Neural Networks.
Neurocomputing, 2013
BMC Bioinform., 2013
Optimizing multiple sequence alignments using a genetic algorithm based on three objectives: structural information, non-gaps percentage and totally conserved columns.
Bioinform., 2013
Intelligent Systems to Autonomously Classify Several Arrhythmia Using Information from ECG.
Proceedings of the International Conference on Social Computing, SocialCom 2013, 2013
Optimal Knots Allocation in Smoothing Splines using intelligent system. Application in bio-medical signal processing. .
Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering, 2013
Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering, 2013
Determining the most suitable multiple sequence alignment methodology by using a set of heterogeneous biological features.
Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering, 2013
Evaluating Multiple Sequence Alignments Using a LS-SVM Approach with a Heterogeneous Set of Biological Features.
Proceedings of the Advances in Computational Intelligence, 2013
Comparison of different computational intelligent classifier to autonomously detect cardiac pathologies diagnosed by ECG.
Proceedings of the 13th International Conference on Intellient Systems Design and Applications, 2013
2012
Optimization of multiple sequence alignment methodologies using a multiobjective evolutionary algorithm based on NSGA-II.
Proceedings of the IEEE Congress on Evolutionary Computation, 2012
2011
Using Machine Learning Techniques and Genomic/Proteomic Information from Known Databases for PPI Prediction.
Proceedings of the 5th International Conference on Practical Applications of Computational Biology & Bioinformatics, 2011
Proceedings of the 5th International Conference on Practical Applications of Computational Biology & Bioinformatics, 2011
Prediction of Functional Associations between Proteins by Means of a Cost-Sensitive Artificial Neural Network.
Proceedings of the Advances in Computational Intelligence, 2011