Software
CANCER EVOLUTION TOOLS
Since 2019, my most recent R packages for Cancer Evolution analyses are hosted at my GitHub Landing page.
TRONCO (TRanslational ONCOlogy) / PiCnIc
An R tool for cancer progression inference from heterogeneous genomic data. TRONCO/PiCnIc has an official website.
Algorithmic methods to infer the evolutionary trajectories in cancer progression. G Caravagna, A Graudenzi, D Ramazzotti, R Sanz-Pamplona, L De Sano, G Mauri , V Moreno, M Antoniotti, B Mishra. PNAS 113 (28), E4025–E4034 2016.
TRONCO: an R package for the inference of cancer progression models from heterogeneous genomic data. L De Sano, G Caravagna, D Ramazzotti, A Graudenzi, G Mauri, B Mishra, M Antoniotti. Bioinformatics 32, 1911-1913, 2016.
Gaussian Processes Correction Maps
Statistical correction of models' outputs via heteroscedastic Gaussian Process regression.Matlab/Python sources: Github repository.
Matching models across abstraction levels with Gaussian Processes. G Caravagna, L Bortolussi, G Sanguinetti. Computational Methods in Systems Biology (CMSB 2016), Lecture Notes in Computer Science 9859, 49-66, 2016.
CoGNaC (Chaste and Gene Networks for Cancer)
A Chaste plugin for the multi-scale simulation of Gene Regulatory Networks driving the spatial dynamics of tissues and cancer. Available at Oxford's Chaste webpage.
CoGNaC: a Chaste plugin for the multiscale simulation of gene regulatory networks driving the spatial dynamics of tissues and cancer. S Rubinacci, A Graudenzi, G Caravagna, J Osborne, J Pitt-Francis, G Maurim M Antoniotti. Cancer Informatics 14 (S4), 53-65, 2015.
NoisySIM (Noisy Simulation)
Simulation of chemically reacting systems with intrinsic and extrinsic bounded noises.Download JAVA sources and the instruction manual.
NoisySIM: exact simulation of stochastic chemically reacting systems with extrinsic noises. G.Caravagna, G.Mauri, A.d'Onofrio. Proc. of the Symposium on Theory of Modeling and Simulation (TMS 2013) 12:1-6, Society for Computer Simulation International, San Diego.
pyTSA (Python Time-Series Analyzer)
A Python tool for the statistical analysis of time-series from stochastic dynamical systems.Python package: Github repository.
Automatising the analysis of stochastic biochemical time-series. G Caravagna, L De Sano, M Antoniotti. BMC Bioinformatics 16(Suppl 9):S8, 2015.
CABERNET/ GESTODifferent
Augmented Boolean Gene Regulatory Networks.This tool has an official website.
CABeRNET: a Cytoscape app for Augmented Boolean models of gene Regulatory NETworks. A.Paroni, A. Graudenzi, G.Caravagna, C.Damiani, G.Mauri, M. Antoniotti. BMC Bioinformatics 17(64), 1-12, 2016.
