Networks have become of central interest in the study of complex biological systems, including the brain. Modern network science approaches are beginning to reveal fundamental principles of brain architecture and function. Connectivity comes in many forms in the architecture and function of human systems - for example, molecular interactions, metabolic pathways, synaptic connections from nano to micro, to meso and macroscopic level. In all cases, the quantitative analysis of connectivity requires sophisticated mathematical and statistical techniques and experimental data from nano to macroscopic levels.  In the talk Prof. Bezerianos will present graph theory models he developed to study: (a)  the intracellular pathways based on  integromics data and (b)  brain networks  dynamics  from EEG and fMRI data. Finally, He presents his proposal for integrating the two approaches towards defining a network medicine framework for brain disorders.

 

Anastasios Bezerianos is a Research Professor in the ECE, National University of Singapore and Senior Principal Research Fellow of Singapore Institute for Neurotechnology (SINAPSE) and Professor at the Medical School of Patras University, Greece. He studied Physics at Patras University and Telecommunications at Athens University, and he received his Ph.D. from the University of Patras. His research interests at large are in Neuroengineering and Systems Medicine and Bioinformatics, and his work is summarized in 101 journal and 153 conference proceedings publications. He has research collaborations with research institutes and universities in Japan, the USA, and Europe, and he is Associate Editor of IEEE TNSRE and the Annals of Biomedical Engineering journals and a reviewer for several international scientific journals. He is a registered expert of the Horizon 2020 program of the European Union and a reviewer of research grant proposals in Italy, Greece, Cyprus and Canada. He is a Senior Member of IEEE and the Founder and Chairman of the biannual International Summer School on Emerging Technologies in Biomedicine.