Topdrim member Matteo Rucco, from Camerino University, presented some of his recent findings on Topological Data Analysis Applied to Idiotypic Network in a meeting at the Institute for Computing Applications (IAC) “M. Picone” – National Council Research.
Matteo Rucco commented on his presentation:
This talk can be considered as the natural evolution of what I discussed in the IPCS satellite of ECCS conference. In the past I used two graph entropies (connectivity and approximate von Neumann) for studying the dynamics of the idiotypic network (a network-based model of the mammal immune system) (IN), here I defined a new entropy, the so-called persistent entropy, that it is based on the persistent intervals of a persistent barcode. We have numerical evidences that this entropy is able to capture the entire dynamics of the IN. For the sake of clarity, this entropy is based on the idea presented in the paper edited by Gonzalez-Diaz et. al, in “an entropy-based persistence barcode”.