Drug Discovery Project
Drug discovery project employing machine learning techniques to predict bioactivity against BRAF. 
Posts by Collection
portfolio
Differential Gene Expression Analysis
Differential gene expression analysis of RNA-Seq data on four human airway smooth muscle cell lines treated with dexamethasone. 
2D Protein Folding Model
Implementation of a simple 2D protein folding model. 
MSc Capstone Project
An image analysis pipeline for detecting different cell phenotypes in breast cancer cells. 
Prediction of the solubility of molecules
Building of a linear regression model for predicting the solubility of molecules. 
Sequence Alignment Algorithms
Implementation and comparison of global and local sequence alignment algorithms.
publications
GADPO: Genetic Algorithm based on Dominance for Primer Optimization
Published in Expert Systems with Applications, 2024
The amplification of the 16S ribosomal RNA gene through the polymerase chain reaction (PCR) is the main approach to profile bacterial communities. This gene is a widely used marker with a composition that allows the identification of microorganisms at the genus or species levels. The correct performance of a PCR assay depends on the properties of the chosen set of primers that match with the target 16S sequences, allowing the amplification by a DNA polymerase. For this reason, optimizing the design of primers attending to such multiple properties is crucial to ensure the specificity and robustness of this process. However, only one multiobjective proposal exists that addresses the optimization of primer design targeted to the 16S gene amplification. Herein, we propose a novel approach for multiobjective primer optimization based on a mutation-based genetic algorithm with three new problem-aware mutation operators, each aimed at covering one of the three objectives that compose the problem (efficiency, coverage, and variability). The proposed algorithm has been tested on 5 real datasets of bacterial 16S gene sequences. The results have been evaluated using 4 quality metrics, showing that our approach achieves statistically significant improvements with regard to the reference multiobjective approach in the field.
Recommended citation: "GADPO: Genetic Algorithm based on Dominance for Primer Optimization". Fernando M. Rodríguez-Bejarano, Miguel A. Vega-Rodríguez, Sergio Santander-Jiménez. Expert Systems With Applications, Volume 238, Part D, 122206, Pergamon-Elsevier Science, Oxford, England, UK, 2024, pp. 1-15, ISSN: 0957-4174. DOI: 10.1016/j.eswa.2023.122206. (JCR impact factor = 8.5 in 2022, Quartile = Q1) https://doi.org/10.1016/j.eswa.2023.122206
talks
Talk 1 on Relevant Topic in Your Field
Published:
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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