Literature DB >> 27354160

BioNSi: A Discrete Biological Network Simulator Tool.

Amir Rubinstein1, Noga Bracha1, Liat Rudner1, Noga Zucker1, Hadas E Sloin1, Benny Chor1.   

Abstract

Modeling and simulation of biological networks is an effective and widely used research methodology. The Biological Network Simulator (BioNSi) is a tool for modeling biological networks and simulating their discrete-time dynamics, implemented as a Cytoscape App. BioNSi includes a visual representation of the network that enables researchers to construct, set the parameters, and observe network behavior under various conditions. To construct a network instance in BioNSi, only partial, qualitative biological data suffices. The tool is aimed for use by experimental biologists and requires no prior computational or mathematical expertise. BioNSi is freely available at http://bionsi.wix.com/bionsi , where a complete user guide and a step-by-step manual can also be found.

Keywords:  biological networks; discrete models; modeling; simulation

Mesh:

Year:  2016        PMID: 27354160     DOI: 10.1021/acs.jproteome.6b00278

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  5 in total

1.  Simulation and visualization of multiple KEGG pathways using BioNSi.

Authors:  Adva Yeheskel; Adam Reiter; Metsada Pasmanik-Chor; Amir Rubinstein
Journal:  F1000Res       Date:  2017-12-11

Review 2.  Systems neuroimmunology: a review of multiomics methodologies to characterize neuroimmunological interactions in spinal and cranial diseases.

Authors:  Cameron Zamanian; Archis R Bhandarkar; Dileep D Monie; F M Moinuddin; Richard G Vile; Alfredo Quiñones-Hinojosa; Mohamad Bydon
Journal:  Neurosurg Focus       Date:  2022-02       Impact factor: 4.332

3.  Interactions between the circadian clock and TGF-β signaling pathway in zebrafish.

Authors:  Hadas E Sloin; Gennaro Ruggiero; Amir Rubinstein; Sima Smadja Storz; Nicholas S Foulkes; Yoav Gothilf
Journal:  PLoS One       Date:  2018-06-25       Impact factor: 3.240

Review 4.  The greater inflammatory pathway-high clinical potential by innovative predictive, preventive, and personalized medical approach.

Authors:  Greg Gibson; Luigi Manni; Christine Nardini; Maria Giovanna Maturo; Marzia Soligo
Journal:  EPMA J       Date:  2019-12-10       Impact factor: 6.543

5.  Systems Analysis of Insulin and IGF1 Receptors Networks in Breast Cancer Cells Identifies Commonalities and Divergences in Expression Patterns.

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

  5 in total

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