Hi! My name is Daniel, and I am a Computer Engineer and Bioinformatician working in the Bioinformatics Unit at CNIO.
I received a Bachelor’s degree in Computer Engineering from the Public University of Navarre (UPNA) in 2018, specializing in Computer Science and Intelligent Systems. My bachelor’s thesis focused on the automatic detection of ocular lesions using computer vision and classification techniques. I then completed a Master’s degree in Bioinformatics and Computational Biology at the Autonomous University of Madrid (UAM), where my master’s thesis focused on predicting intrapartum fetal hypoxia using machine learning.
In November 2019, I joined the CNIO Bioinformatics Unit as a member of the GENCODE project under the supervision of Michael Tress. My work involved processing and analyzing large-scale proteomics datasets and managing the APPRIS and FireDB databases for principal protein isoform prediction and ligand annotation. Also, under the leadership of Fátima Al-Shahrour, I have been developing and maintaining bioinformatics workflows, implementing data management and visualization tools, and providing administration and user support for the institution’s HPC cluster.
I have always been passionate about biology and human health, and I would like to continue building my career in this field by applying my expertise in machine learning to address challenges in cancer biology while further developing my research and computational skills.
