Dr Inti Anabela Pagnuco

• PhD in Electronic Engineering 2016, School of Engineering, National University of Mar del Plata, Argentina
• BSc in Bioinformatic 2010, School of Engineering, National University of Entre Ríos, Argentina

Dr Pagnuco received a degree in Bioinformatics in 2010 from the School of Engineering, National University of Entre Ríos, Argentina. In 2016, she received a PhD in Electronic Engineering from the School of Engineering at the National University of Mar del Plata (UNMdP). Her research topic was 'Supervised classification techniques applied to high-density genetic data'.

She worked as teaching assistant in the area of Applied Mathematics and informatics, assigned to the courses “Algorithms and Data Structures”, “Basic Statistic”, “Programming”, “Numerical Methods” and “Data Bases” in the School of Engineering of the National University of Mar del Plata, Argentina.

In 2018, she did a postdoctoral experience at System Biology Ireland, University College Dublin. The focus of the project was to build a dynamic modeling of the interconnected p53/p63/p73 DNA damage response network and consider the p53 mutant status. The model was applied to breast cancer data through patient-specific simulations to predict clinical outcomes as patient survival and clinical drug-response.

Dr Pagnuco's research involves generating genome-wide distribution of cis-regulatory elements, in particular enhancers and exploring the mechanism of gene-expression programs using mathematical modelling and quantitative methods such as the iterative Random Forest (iRF). Specifically, her aim is to use machine learning to predict the functional activity of cis-regulatory elements genome-wide, using ChIP-seq, DNase-seq, digital footprinting, and motifs as inputs and use validated enhancer elements as training sets.

Research Groups and Centres

Centre for Computational Biology