Topological Indices (TIs) are numerical parameters useful to carry out Quantitative Structure-Property Relationships (QSPR)
analysis and predict the effect of perturbations in many types of Complex Networks. This work, focuses on a very powerful class of TIs
called Galvez charge transfer indices. First, we review the classic concept and some applications of these indices. Next, we review the
Galvez-Markov TIs of order k (GMk), a recent generalization to these TIs introduced by us. We also reviewed some previous examples of
calculation of GMk values for different classes of networks, including metabolic networks. Here, we also demonstrated that Galvez-
Markov TIs are useful to predict perturbations and the transferability of biochemical patterns forms metabolic networks of species to others.
We report a linear QSPR-Perturbation theory model that predicts more than 300,000 perturbations in metabolic networks with 85 –
99% of good classification in training and validation series.
Keywords: Complex networks, QSAR, topological indices, metabolic networks, markov chains.
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