Affiliation:
1. Computer Science Department , Sapienza University of Rome , Rome , Italy ,
2. LUISS University , Rome , Italy ,
Abstract
Abstract
Many important aspects of biological knowledge at the molecular level can be represented by pathways. Through their analysis, we gain mechanistic insights and interpret lists of interesting genes from experiments (usually omics and functional genomic experiments). As a result, pathways play a central role in the development of bioinformatics methods and tools for computing predictions from known molecular-level mechanisms. Qualitative as well as quantitative knowledge about pathways can be effectively represented through biochemical networks linking the biochemical reactions and the compounds (e.g., proteins) occurring in the considered pathways. So, repositories providing biochemical networks for known pathways play a central role in bioinformatics and in systems biology. Here we focus on Reactome, a free, comprehensive, and widely used repository for biochemical networks and pathways. In this paper, we: (1) introduce a tool StARGate-X (STatistical Analysis of the Reactome
multi-GrAph Through
nEtworkX) to carry out an automated analysis of the connectivity properties of Reactome biochemical reaction network and of its biological hierarchy (i.e., cell compartments, namely, the closed parts within the cytosol, usually surrounded by a membrane); the code is freely available at https://github.com/marinoandrea/stargate-x; (2) show the effectiveness of our tool by providing an analysis of the Reactome network, in terms of centrality measures, with respect to in- and out-degree. As an example of usage of StARGate-X, we provide a detailed automated analysis of the Reactome network, in terms of centrality measures. We focus both on the subgraphs induced by single compartments and on the graph whose nodes are the strongly connected components. To the best of our knowledge, this is the first freely available tool that enables automatic analysis of the large biochemical network within Reactome through easy-to-use APIs (Application Programming Interfaces).
Funder
Sapienza Università di Roma
European Commission
Reference45 articles.
1. AMICI. 2021. Available from: https://amici.readthedocs.io/en/latest/about.html.
2. BioSCRAPE: bio circuit stochastic single-cell reaction analysis and parameter estimation. 2017. Available from: https://github.com/biocircuits/bioscrape/.
3. COPASI: biochemical system simulator. 2006 Available from: http://copasi.org.
4. LibRoadRunner. 2015 Available from: https://www.libroadrunner.org/.
5. Hucka, M,Finney, A,Sauro, HM,Bolouri, H,Doyle, JC,Kitano, H, et al.. The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 2003;19:524–31.