As the Head of Bioinformatics at Duponte, a pioneering startup in pharmacogenomics, I'm leading the development and establishment of our in-house bioinformatics lab. My role involves creating and scaling bioinformatics services tailored for internal research, managing partnerships with public research institutions, and designing training programs to advance bioinformatics knowledge within the team. By combining technical expertise with strategic partnerships, I’m driving research initiatives that support Duponte’s mission to transform personalized medicine through cutting-edge pharmacogenomic solutions.

As a member of the Computational Systems Medicine group, my work revolves around decoding complex genomic data. In this multidisciplinary team of experts in biology, medicine, mathematics, statistics, and computer engineering, we collaboratively model disease mechanisms and drug actions. My role is centered on utilizing omics data, clinical insights, and real-world information through mathematical modeling and AI in the intriguing field of systems biology.

As a member of the Computational Systems Medicine group, my work revolves around decoding complex genomic data. In this multidisciplinary team of experts in biology, medicine, mathematics, statistics, and computer engineering, we collaboratively model disease mechanisms and drug actions. My role is centered on utilizing omics data, clinical insights, and real-world information through mathematical modeling and AI in the intriguing field of systems biology.

Interning at Sapienza University, delving into cancer pathways & Signor models. Implementing these in Hipathia tool to analyze cancer transcriptomic data.

I successfully completed an internship with the Protein Function Development group at EMBL-EBI. During this experience, I focused on leveraging transcriptomic data from different tissues to model signal transduction and gained insights into indirect protein effects on diverse signaling circuits using correlation-based tests. Our project aimed to enhance our understanding of protein function across various tissues and its impact on signaling pathways.

I specialize in Proteomics and Proteogenomics analysis, driving advancements through algorithm development and pipeline optimization. Proficient in statistical analysis, my expertise extends to characterizing disease parameters using diverse datasets, including Microarrays, RNA-Seq, Exome Sequencing, and single-cell RNA-seq data.

I am a dedicated Professor in Bioinformatics Analysis, specializing in Functional Analysis of Genes and Gene Ontology Enrichment at UPO. My approach integrates real-world examples, ensuring a dynamic learning environment that equips students with practical skills in bioinformatics.

In my dual role within the Tay-Sachs and Sandhoff diseases research projects, I orchestrated simultaneous investigations into the underlying physiopathology of both conditions. My responsibilities included conducting microarrays analyses on patients and rodent models affected by Tay-Sachs and Sandhoff, unraveling molecular signatures crucial for understanding these diseases. Simultaneously, I delved into the intricate metabolic pathways associated with each condition, providing a comprehensive understanding of their distinct biochemical mechanisms. My work involved analyzing clinical histories of affected individuals, contributing valuable insights into disease progression for both Tay-Sachs and Sandhoff. This dual-disease focus showcased my ability to navigate and contribute to complex research endeavors concurrently, advancing our understanding of these rare conditions.

In my role, I've made key contributions by investigating metabolic network structures using advanced techniques such as Elementary Flux Modes (EFMs) and Minimal Cut Sets (MCS) algorithms. Additionally, I bring expertise in skillfully applying parallel coordinates to visually represent intricate information on network structure and topology. Notable accomplishments include the successful application of EFMs and MCS algorithms to unravel complex metabolic pathways.

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