Simulation and visualization of multiple KEGG pathways using BioNSi

Abstract

Motivation: Many biologists are discouraged from using network simulation tools because these require manual, often tedious network construction. This situation calls for building new tools or extending existing ones with the ability to import biological pathways previously deposited in databases and analyze them, in order to produce novel biological insights at the pathway level. Results: We have extended a network simulation tool (BioNSi), which now allows merging of multiple pathways from the KEGG pathway database into a single, coherent network, and visualizing its properties. Furthermore, the enhanced tool enables loading experimental expression data into the network and simulating its dynamics under various biological conditions or perturbations. As a proof of concept, we tested two sets of published experimental data, one related to inflammatory bowel disease condition and the other to breast cancer treatment. We predict some of the major observations obtained following these laboratory experiments, and provide new insights that may shed additional light on these results. Tool requirements: Cytoscape 3.x, JAVA 8 Availability: The tool is freely available at http://bionsi.wix.com/bionsi, where a complete user guide and a step-by-step manual can also be found.

Rapid Identification of Druggable Targets and the Power of the Phenotype SIMulator for Effective Drug Repurposing in COVID-19

“…Furthermore, since pharmacological treatments may depend on the state of biological processes, PHENSIM may be of more appropriate use in this context. Comparison with other simulation algorithms such as BIONSI 13,14 has shown excellent performance by PHENSIM 15 . PHENSIM creates and builds on interpretable and intervenable mechanistic bio-chemical models, rather than combinatorial and statistical "black-box" models for joint stationary distribution of biological data, as in, say proteinprotein interaction (PPI) networks, Graphical or Deep-net models.…”

“…It is becoming evident that treatment should not only focus on direct antiviral effects in mild cases but should also encompass potential (cytokine storm induced) aberrant host-response in severe cases 4,11,12 . Taken together, this points towards the importance of a more detailed and targeted approach for COVID-19, where antivirals or steroids alone might not suffice and specifically targeting the (aberrant) host-response is imperative 4,7,8 .Recently in literature, tools and algorithms devised to perform simulation on biological networks have been described 13,14 . Here we aim to utilize our systems biology tool, the PHENotype SIMulator (PHENSIM), to leverage the power of pathway analysis by simulating tissue-specific infection of host cells of SARS-CoV-2 and subsequently perform in silico drug selection for potential repurposing.…”

“…Recently in literature, tools and algorithms devised to perform simulation on biological networks have been described 13,14 . Here we aim to utilize our systems biology tool, the PHENotype SIMulator (PHENSIM), to leverage the power of pathway analysis by simulating tissue-specific infection of host cells of SARS-CoV-2 and subsequently perform in silico drug selection for potential repurposing.…”

Application of the PHENotype SIMulator for rapid identification of potential candidates in effective COVID-19 drug repurposing

“…Recently in literature, tools and algorithms devised to perform simulation on biological networks have been described [ 17 , 18 ]. Here we aim to utilize our systems biology tool, the PHEN otype SIM ulator (PHENSIM) [ 19 ], to leverage the power of pathway analysis by simulating tissue-specific infection of host cells of SARS-CoV-2 and subsequently perform in silico drug selection for potential repurposing.…”

PHENSIM: Phenotype Simulator

“…Boolean networks [ 5 , 6 ] and Petri nets [ 7 ] represent two types of discrete models. BioNSi (Biological Network Simulator) [ 8 ] is an intuitive model, implemented as a Cytoscape 3 plugin [ 9 ]. It can use KEGG pathways [ 10 ] as a network model and represents each element in discrete states (usually up to 10).…”