title: The Rücker-Markov invariants of complex Bio-Systems: applications in Parasitology and Neuroinformatics.
abstract: Rücker's walk count (WC) indices are well-known topological indices (TIs) used in Chemoinformatics to quantify the molecular structure of drugs represented by a graph in Quantitative structure-activity/property relationship (QSAR/QSPR) studies. In this work, we introduce for the first time the higher-order (kth order) analogues (WCk) of these indices using Markov chains. In addition, we report new QSPR models for large complex networks of different Bio-Systems useful in Parasitology and Neuroinformatics. The new type of QSPR models can be used for model checking to calculate numerical scores S(Lij) for links Lij (checking or re-evaluation of network connectivity) in large networks of all these fields. The method may be summarized as follows: (i) first, the WCk(j) values are calculated for all jth nodes in a complex network already created; (ii) A linear discriminant analysis (LDA) is used to seek a linear equation that discriminates connected or linked (Lij=1) pairs of nodes experimentally confirmed from non-linked ones (Lij=0); (iii) The new model is validated with external series of pairs of nodes; (iv) The equation obtained is used to re-evaluate the connectivity quality of the network, connecting/disconnecting nodes based on the quality scores calculated with the new connectivity function. The linear QSPR models obtained yielded the following results in terms of overall test accuracy for re-construction of complex networks of different Bio-Systems: parasite-host networks (93.14%), NW Spain fasciolosis spreading networks (71.42/70.18%) and CoCoMac Brain Cortex co-activation network (86.40%). Thus, this work can contribute to the computational re-evaluation or model checking of connectivity (collation) in complex systems of any science field.
authors: Department of Organic Chemistry II, Faculty of Science and Technology, Euskal Heriko Univertsitatea (UPV/EHU), Leioa, 48940, Bizkaia, Basque Country, Spain.
authors: Humberto
authors: H
authors: González-Díaz
authors: Pablo
authors: P
authors: Riera-Fernández
authors: Alejandro
authors: A
authors: Pazos
authors: Cristian R
authors: CR
authors: Munteanu
mesh_terms: D000818:Animals; D001921:Brain / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D016002:Discriminant Analysis; D006790:Host-Parasite Interactions; D008251:Macaca; D008390:Markov Chains; D008954:Models, Biological; D009462:Neurology / Q000379:methods*; D010274:Parasitology / Q000379:methods*; D021281:Quantitative Structure-Activity Relationship; D014201:Trematode Infections / Q000453:epidemiology