The Randic index is a well known topological index (TI) used in QSAR/QSPR studies to quantify the
molecular structure represented by a graph. In this work we review some aspects of this TI with special emphasis on the
generalizations introduced by Kier & Hall and more recently by Estrada. Next, we introduced a new generalization using a
Markov chain in order to obtain a new family of TIs called the Markov-Randi indices of order k-th (1χk). Later, we
applied these new indices to seek models useful to calculate numerical quality scores S(Lij) for network links Lij
(connectivity) in known complex networks. The linear models obtained produced the following results in terms of overall
accuracy for network re-construction: Metabolic networks (70.48%), Parasite-Host networks (90.86%), CoCoMac brain
cortex co-activation network (81.59%), NW Spain Fasciolosis spreading network (99.04%). Spanish financial law
network (71.83%). This work opens a new door to the computational re-evaluation of network connectivity quality
(collation) in different complex systems.
Keywords: Brain cortex networks, complex networks, connectome, disease spreading networks, legal-social networks, markov
chains, metabolic reactions networks, quantitative structure-property relationships, topological indices.
Rights & PermissionsPrintExport