:: DESCRIPTION
piNet is a resource for interactively exploring modular network models of plant immune response.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
NO
:: MORE INFORMATION
Citation:
Dong X., Jiang Z., Peng Y-L., Zhang Z. (2015)
Revealing Shared and Distinct Gene Network Organization in Arabidopsis Immune Responses by Integrative Analysis.
Plant Physiol. 2015 Mar;167(3):1186-203. doi: 10.1104/pp.114.254292.
:: DESCRIPTION
InterSPPI is a web server that could predict protein-protein interactions (PPIs) between Arabidopsis thaliana and pathogens based on sequence and Arabidopsis thaliana intra-species PPI network (AraPPI) information.
::DEVELOPER
Ziding Zhang’s Lab, China Agricultural University
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Brief Bioinform. 2019 Jan 18;20(1):274-287. doi: 10.1093/bib/bbx123.
Critical assessment and performance improvement of plant-pathogen protein-protein interaction prediction methods.
Yang S, Li H, He H, Zhou Y, Zhang Z.
:: DESCRIPTION
RocketBugs is a simulation of the actin-based motility of Listeria monocytogenes.
RocketBugsRender is a special rendering and graphing program for the simulation output of “RocketBugs”, the actin-based Listeria motility simulations
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Susanne M. Rafelski, Jonathan B. Alberts, Garrett M. Odell
An Experimental and Computational Study of the Effect of ActA Polarity on the Speed of Listeria monocytogenes Actin-based Motility
PLoS Comput Biol 5(7): e1000434. doi:10.1371/journal.pcbi.1000434
:: DESCRIPTION
ParMSpindle is a 3D, force-based simulation of the ParM mediated segregation of bacterial plasmids, tracking the biochemical state of each monomer with experimentally determined filament dynamics
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
:: DESCRIPTION
Odefy is a MATLAB- and Octave-compatible toolbox for the automated transformation of Boolean models into systems of ordinary differential equations.
::DEVELOPER
Institute of Computational Biology, German Research Center for Environmental Health (GmbH)
:: SCREENSHOTS
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Krumsiek J, Poelsterl S, Wittmann DM, Theis FJ.
Odefy – From discrete to continuous models.
BMC Bioinformatics. 2010, 11:233.
:: DESCRIPTION
simbTUM allows to define ODE-models or stochastic compartemental models of biological processes, to simulate, to fit data and to do some statistics (fitting and statistics for deterministic models only).
::DEVELOPER
Institute of Computational Biology, German Research Center for Environmental Health (GmbH)
:: SCREENSHOTS
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
:: DESCRIPTION
iVUN is a visualization toolbox which supports uncertainty-aware analysis of static and dynamic attributes of biochemical reaction networks
::DEVELOPER
:: SCREENSHOTS
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
C. Vehlow, J. Hasenauer, A. Kramer, J. Heinrich, N. Radde, F. Allgoewer, and D. Weiskopf.
Uncertainty-aware visual analysis of biochemical reaction networks.
In Proceedings of IEEE Symposium on Biological Data Visualization(Biovis), pages 91–98, 2012.
:: DESCRIPTION
TSNI assumes that the gene network can be modeled by the following system of ordinary differential equation to represent the rate of synthesis of a transcript as a function of the concentrations of every other transcript in a cell and the external perturbation.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
IET Syst Biol. 2007 Sep;1(5):306-12.
Inference of gene networks from temporal gene expression profiles.
Bansal M, di Bernardo D.
:: DESCRIPTION
The MNI (Mode-of-action by Network Inference ) is an algorithm to identify the gene targets of a drug treatment based on gene-expression data. In a typical use of the algorithm, a single expression profile, say obtained as a result of a treatment under study, is used as the test profile while a set of hundreds of expression profiles is used as the training set. The MNI algorithm uses the large training data set of expression profiles to construct a statistical model of gene-regulatory networks in a cell or tissue. The model describes combinatorial influences of genes on one another.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Nat Protoc. 2006;1(6):2551-4.
The mode-of-action by network identification (MNI) algorithm: a network biology approach for molecular target identification.
Xing H, Gardner TS.
:: DESCRIPTION
In order to estimate the coefficient of the gene interactions NIR solves a linear regression problem for each gene considering a fixed number of k regressors. The regressor set is chosen according the residual sum of square error (RSS) minimization criterion. In this version, NIR exhaustively searches the best regressors in the space of all the possible k-tuples of genes.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Pac Symp Biocomput. 2004:486-97.
Robust identification of large genetic networks.
Di Bernardo D, Gardner TS, Collins JJ.