Computational and Quantitative Biology PhD

My name is Vincenzo Aievola and I am a Molecular and Industrial Biotechnologist.
During my studies I had the chance to gain knowledge about genetic, molecular and biochemical features of different living forms, focusing the attention on microorganisms.
More specifically, I studied how to exploit them in order to produce (either naturally or in a recombinant way) a wide range of molecules (enzymes and other proteins, saccharides, other types of primary and secondary metabolites) useful in different fields of human life (e.g. food, health, energy).
I can summarize my work experiences in two university internships, essential for my bachelor and master dissertations:

• In my first internship, accomplished in the lab of prof. Daria Maria Monti, I gained technical expertise regarding the cultivation of microalgae and the extraction of natural antioxidant compounds.
• During my second internship, accomplished in the lab of prof. Maria Luisa Tutino, I gained technical expertise regarding the optimization of recombinant protein expression using the psychrophilic bacterium Pseudoalteromonas haloplanktis TAC125 (PhTAC125) as host. Moreover, I could also perform an in-silico analysis of the replication origin sequence that characterizes the expression system used. This step brought out great interest in the application of computer science in biology.

Furthermore, after the graduation, I attended online courses promoted by Coursera and the University of London, regarding the basis of Machine Learning and AI to further my knowledge about these impressive science fields and better understand how they could be applied to resolve life science’s challenges and help research. At present, I'm a PhD student in Computational and Quantitative Biology. During my first month of experience, accomplished in the lab of prof. Mario Capasso, I focused the attention on the use of next-generation sequencing, WES and RNA-Seq to decode the tumor genome and identify cancer genes related to Neuroblastoma onset.