## 4 Conclusions  
This work confirms that Markov chains are useful to calculate Shannon entropy information indices \(\text{Sh}_{\text{k}}\) that quantify the connectivity patterns on both BCNs and ANNs. We demonstrated how to develop Net-Net AutoML models based on \(\text{Sh}_{\text{k}}\) values of both networks. The dataset contains 500,470 examples and 20 features. Twelve linear and non-linear Machine Learning classifiers were tested and the best classification model was provided by Random Forest (50 trees) with the mean test AUROC of 0.9991 \(\pm\) 0.0001 (10-fold cross-validation). The Net-Net AutoML models are useful to determine the ANN topology, which is better to predict the connectivity in the BCN system. Consequently, we can use this methodology to predict the ANN topologies, with better performance before training them. This may lead to an optimization of computing resources. The scripts and dataset for this project are available in an open GitHub repository from one of the authors, [PERSON] [63].  
Conceptualization, C.R.M. and H.G.-D.; methodology, C.R.M.; software, C.R.M.; data analysis with Machine Learning and scripting, C.R.M., M.G., J.R.R., and J.D.; writing--original draft preparation, C.R.M. and E.B.; data curation, E.B., C.R.M., and H.G.-D., writing--review and editing, C.R.M., M.G., J.R.R., and J.D.; visualization, C.R.M. and A.P.; validation, J.D., J.R.R., M.G., H.G.-D., and A.P.; supervision, A.P., J.R.R., M.G., and [PERSON]; project administration, [PERSON], [PERSON], and [PERSON]; funding acquisition, A.P. All authors have read and agreed to the published version of the manuscript.  
This research and the APC were funded by Consolidation and Structuring of Competitive Research Units--Competitive Reference Groups (ED431C 2018/49) funded by the Ministry of Education, University and Vocational Training of Xunta de Galicia endowed with EU FEDER funds.  
The authors acknowledge Instituto de Salud Carlos III, grant number PI17/01826 (Collaborative Project in Genomic Data Integration (CICLOGEN) funded by Instituto de Salud Carlos III from the Spanish National plan for Scientific and Technical Research and Innovation 2013-2016 and the European Regional Development Funds (FEDER)--A way to build Europe.\"). Authors also acknowledge the Basque Government (Eusko Jaurlaritza) grant (IT1045-16)--2016-2012 for consolidated research groups. This project was also supported by the General Directorate of Culture, Education and University Management of Xunta de Galicia ED431D 2017/16, the \"Drug Discovery Galian Network\". ERD431G/01, the \"Galician Network for Colorectal Cancer Research\" (Ref. ED431D 2017/23), and finally by the Spanish Ministry of Economy and Competitiveness through the project BLA2017-86738-R and through the funding of the unique installation BIOCAI (UNLC08-IE-002, UNLC13-13-3503) and the European Regional Development Funds (FEDER) by the European Union. Additional support was offered by the Accreditation, Structuring, and Improvement of Consolidated Research Units and  
Figure 4: Feature importance for the best Random Forest model.  
Singular Centers (ED431G/01), funded by the Ministry of Education, University and Vocational Training of Xunta de Galicia endowed with EU FEDER funds. Last, the authors also acknowledge research grants from the Ministry of Economy and Competitiveness, MINECO, Spain (FEDER CTQ2016-74881-P) and support of Ikerbasque, the Basque Foundation for Science.  
The authors declare no conflict of interest.