Previous training and experience
My methodological and theoretical research as well as a considerable portion of my applied and collaborative work during my postgraduate studies addressed computational biology and risk factors associated with the progress of Coronary Heart Diseases (CHDs). An innovative contribution of my work is the establishment of a new perspective to the analysis of plasma lipidome variables in the prediction of CHDs, and taking advantage of Artificial Neural Network (ANN) and genetic algorithm to develop a new model of disease prediction that is more accurate than the previous automated models. This perspective creates a new class of functional estimation procedures that account for the within-subject correlation in an intuitive and efficient manner.
Why you wanted to join the project
I was fascinated with the aspirations of the COL_RES Training Network because I wanted to focus my research on the question of how to leverage analytical techniques and models to develop new tools for the diagnosis and treatment of microbiota-related disorders and wished to be at the heart of leading research of the human microbiome and dedicate my time and energy to contributing to the scientific community.
About your research project
During my project as an early stage researcher, I will be working on existing and COL_RES datasets to identify the most discriminative features and predict outcomes by applying multidimensional scaling, multivariate statistics and hierarchical clustering to cross-correlate phageome, microbiota, and metabolome profiles. This will include state-of-the-art engineering and predictive modeling techniques such as Kernel Machines and Deep Learning algorithms, incorporating ‘omics’ datasets to classify a combination of features that jointly best predict colonization resistance.
Other Interests
My hobbies are hiking and going to the movies on the weekends. I enjoy socializing with my friends and playing board games together. I also love reading books about philosophy and developmental psychology.
Contact details: KKakaBra@ucc.ie
