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.
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.
Authors: Nikolay Kolesnikov; Emma Hastings; Maria Keays; Olga Melnichuk; Y Amy Tang; Eleanor Williams; Miroslaw Dylag; Natalja Kurbatova; Marco Brandizi; Tony Burdett; Karyn Megy; Ekaterina Pilicheva; Gabriella Rustici; Andrew Tikhonov; Helen Parkinson; Robert Petryszak; Ugis Sarkans; Alvis Brazma Journal: Nucleic Acids Res Date: 2014-10-31 Impact factor: 16.971
Authors: Alessandro Di Cara; Abhishek Garg; Giovanni De Micheli; Ioannis Xenarios; Luis Mendoza Journal: BMC Bioinformatics Date: 2007-11-26 Impact factor: 3.169
Authors: Stefano Schivo; Jetse Scholma; Paul E van der Vet; Marcel Karperien; Janine N Post; Jaco van de Pol; Rom Langerak Journal: BMC Syst Biol Date: 2016-07-27
Authors: Rive Sarfstein; Adva Yeheskel; Tali Sinai-Livne; Metsada Pasmanik-Chor; Haim Werner Journal: Front Endocrinol (Lausanne) Date: 2020-07-07 Impact factor: 5.555