In the field of science I mainly working with transcription factors. I am trying to understand how the different mutation variants (mainly Single Nucleotide Polymorphisms - SNPs) can affect and change the binding site of the different transcription factors. Furthermore I am investigating how these binding site changes can affect on the downstream genomic processes and mechanisms (for example gene expression).
Because of the large amount of data I work with I am interested in the filed of Big Data.The definition of Big Data is the data that contains greater variety, arriving in increasing volumes and with more velocity. This is also known as the three Vs (Volume, Velocity, Variety). Recently we have published a Big Data based platform in the F1000Research journal, called Sherlock (Bohar et al, F1000Research, 2022). This platform has a lot of valuable features: 1) store all datasets in redundant and organized cloud storage; 2) convert all datasets to standard, optimized file formats; 3) execute analytical queries on top of data files; 4) share datasets among different teams/projects; 5) generate operational datasets for particular services or collaborators; 6) provides a storage solution for big data computational biology projects.
Regarding my hobbies: I like playing football, playing with different video games, running, reading and of course programming.