Biomedicine, supercomputers and simulations: in silico experiments and its applications in cancer research
Computational simulations of cellular processes (e.g. metabolism, gene expression, signal transduction) are critical tools to formulate mechanistic explanations that facilitate the interpretation of experimental results. However, complex biological processes such as tumour evolution span across...
Scientific topics: Molecular interactions, pathways and networks, Personalised medicine, Simulation experiment
Operations: Modelling and simulation
Keywords: HPC, Biomodelling, cell simulations
Resource type: Webinar
Biomedicine, supercomputers and simulations: in silico experiments and its applications in cancer research
https://www.youtube.com/watch?v=x1zCn0-oeQQ
http://tess.elixir-uk.org/materials/biomedicine-supercomputers-and-simulations-in-silico-experiments-and-its-applications-in-cancer-research
Computational simulations of cellular processes (e.g. metabolism, gene expression, signal transduction) are critical tools to formulate mechanistic explanations that facilitate the interpretation of experimental results. However, complex biological processes such as tumour evolution span across different time-space scales. For instance, a population-level description is needed to account for genetic heterogeneity and phenotypic variability due to environmental noise, whereas intracellular models, such as cell signalling networks need to address the effect of mutated genes. In this context, multi-scale models are ideal tools to address systems biology questions as they can consider several time-space scales by combining different approaches into a hybrid simulation.
PhysiCell is an open-source, agent-based extensible multi-scale modelling framework that allows simulating complex multicellular systems such as healthy tissues and tumours.
Miguel Ponce de León
Molecular interactions, pathways and networks
Personalised medicine
Simulation experiment
HPC, Biomodelling, cell simulations
Anyone interested in simulation of metabolic models, and in PerMedCoE tools and activities
Tutorials on COBREXA
COBREXA.jl provides tutorials and notebooks with the purpose of explaining the most important concepts and functions for metabolic modelling and model handling to users, and then practicing them.
The documentation contains basic tutorials (explaining the core package concepts and basic design...
Scientific topics: Simulation experiment, Personalised medicine
Operations: Modelling and simulation
Keywords: cell-level simulations, Biomodelling, HPC
Resource type: Tutorial
Tutorials on COBREXA
https://lcsb-biocore.github.io/COBREXA.jl/stable/
http://tess.elixir-uk.org/materials/tutorials-on-cobrexa
COBREXA.jl provides tutorials and notebooks with the purpose of explaining the most important concepts and functions for metabolic modelling and model handling to users, and then practicing them.
The documentation contains basic tutorials (explaining the core package concepts and basic design ideas), advanced tutorials (describing complicated functionality required for optimised execution of large analyses) and Jupyter notebooks that demonstrate the concepts from tutorials in a more practical setting, with realistic data.
Miroslav Kratochvil
Laurent Heirendt
St Elmo Wilken
Simulation experiment
Personalised medicine
cell-level simulations, Biomodelling, HPC
Tutorial on CellNOpt
This tutorial aims to be an introduction to
i) the preparation of the Prior knowledge network (PKN) of signaling pathways and
ii) the training of the PKN against biochemical data to create cell-specific models.
Scientific topics: Molecular interactions, pathways and networks, Simulation experiment, Personalised medicine
Operations: Modelling and simulation
Keywords: HPC, Biomodelling, Signalling
Resource type: Tutorial
Tutorial on CellNOpt
https://saezlab.github.io/CellNOptR/2_usage/
http://tess.elixir-uk.org/materials/tutorial-on-cellnopt
This tutorial aims to be an introduction to
i) the preparation of the Prior knowledge network (PKN) of signaling pathways and
ii) the training of the PKN against biochemical data to create cell-specific models.
Bartosz Bartmanski
Molecular interactions, pathways and networks
Simulation experiment
Personalised medicine
HPC, Biomodelling, Signalling
Introduction to qualitative modelling with MaBoSS
Boolean modelling uses a simple representation of biological entities as either active or inactive, and describes their relations with logical formulas. MaBoSS extends Boolean modelling by adding a notion of continuous time, with the introduction of rates of (in)activation. This enable the...
Scientific topics: Statistics and probability, Molecular interactions, pathways and networks, Personalised medicine, Simulation experiment
Operations: Modelling and simulation
Keywords: HPC, Biomodelling, cell simulations, Boolean
Resource type: Webinar
Introduction to qualitative modelling with MaBoSS
https://www.youtube.com/watch?v=zvOZBFivpCc
http://tess.elixir-uk.org/materials/introduction-to-qualitative-modelling-with-maboss
Boolean modelling uses a simple representation of biological entities as either active or inactive, and describes their relations with logical formulas. MaBoSS extends Boolean modelling by adding a notion of continuous time, with the introduction of rates of (in)activation. This enable the representation of physical time, and of processes with different time scales. MaBoSS simulate multiple stochastic trajectories, and produces trajectories of the probabilities of the system state. This webinar will introduce the concepts of boolean modelling, and MaBoSS’ continuous time boolean modelling, and will then demonstrate the use of WebMaBoSS, a web interface designed for easily simulating MaBoSS models.
Vincent Noel
Statistics and probability
Molecular interactions, pathways and networks
Personalised medicine
Simulation experiment
HPC, Biomodelling, cell simulations, Boolean
Anyone interested in simulation of metabolic models, and in PerMedCoE tools and activities
runBioSimulations tutorial and help
runBioSimulations is a web application for executing a broad range of modeling studies and visualizing their results. runBioSimulations uses BioSimulators to supports a broad range of modeling frameworks (e.g., logical, constraint-based, kinetic), simulation algorithms (e.g., CVODE, FBA, SSA),...
Scientific topics: Simulation experiment, Computational biology, Systems biology
Operations: Modelling and simulation
Keywords: biosimulators, COMBINE, OMEX, SED-ML, Modeling, dynamic simulations, SBML, BNGL
Resource type: Tutorial, Documentation
runBioSimulations tutorial and help
https://run.biosimulations.org/help
http://tess.elixir-uk.org/materials/runbiosimulations-tutorial-and-help
runBioSimulations is a web application for executing a broad range of modeling studies and visualizing their results. runBioSimulations uses BioSimulators to supports a broad range of modeling frameworks (e.g., logical, constraint-based, kinetic), simulation algorithms (e.g., CVODE, FBA, SSA), and modeling formats (e.g., BNGL, SBML). runBioSimulations also provides a REST API for programmatic access to the same simulation capabilities.
The runBioSimulations tutorial and help describes how to use this web application and web service to execute simulations and visualize their results. This includes instructions on how to create COMBINE/OMEX archives of modeling projects.
Jonathan Karr
Ion Moraru
Bilal Shaikh
Gnaneswara Marupilla
Simulation experiment
Computational biology
Systems biology
biosimulators, COMBINE, OMEX, SED-ML, Modeling, dynamic simulations, SBML, BNGL
modelers
BioSimulators tutorial and help
BioSimulators is a registry of containerized biosimulation tools that provide consistent command-line interfaces. The BioSimulations web application helps investigators browse this registry to find simulation tools that have the capabilities (supported modeling frameworks, simulation algorithms,...
Scientific topics: Simulation experiment, Computational biology, Systems biology
Operations: Modelling and simulation
Keywords: Modeling, biomodel, dynamic simulations, COMBINE, OMEX, SED-ML, SBML, BNGL
Resource type: Tutorial, Documentation
BioSimulators tutorial and help
https://biosimulators.org/help
http://tess.elixir-uk.org/materials/biosimulators-help
BioSimulators is a registry of containerized biosimulation tools that provide consistent command-line interfaces. The BioSimulations web application helps investigators browse this registry to find simulation tools that have the capabilities (supported modeling frameworks, simulation algorithms, and modeling formats) needed for specific modeling projects.
The BioSimulators help describes how to use this registry:
- How to find a containerized simulation tools that are capable of executing a modeling study.
- How to use containerized simulation tools to execute modeling studies.
- How to containerize a simulation tool and submit it to the BioSimulators registry.
Jonathan Karr
Ion Moraru
Bilal Shaikh
Simulation experiment
Computational biology
Systems biology
Modeling, biomodel, dynamic simulations, COMBINE, OMEX, SED-ML, SBML, BNGL
modelers
Computational biologists
software developers, bioinformaticians
DE-Sim examples, tutorials, and documentation
*DE-Sim* is an open-source, Python-based object-oriented discrete-event simulation (DES) tool that makes it easy to use large, heterogeneous datasets and high-level data science tools such as [NumPy](https://numpy.org/), [Scipy](https://scipy.org/scipylib/index.html),...
Scientific topics: Computational biology, Mathematics, Computer science, Simulation experiment
Operations: Visualisation, Modelling and simulation
Keywords: data-driven modeling, Computational modelling, discrete-event simulation, DES, object-oriented programming, Python, data visualization, Data Science
Resource type: examples, Tutorial, Jupyter notebook, API reference
DE-Sim examples, tutorials, and documentation
https://github.com/KarrLab/de_sim
http://tess.elixir-uk.org/materials/de-sim-examples-tutorials-and-documentation
*DE-Sim* is an open-source, Python-based object-oriented discrete-event simulation (DES) tool that makes it easy to use large, heterogeneous datasets and high-level data science tools such as [NumPy](https://numpy.org/), [Scipy](https://scipy.org/scipylib/index.html), [pandas](https://pandas.pydata.org/), and [SQLAlchemy](https://www.sqlalchemy.org/) to build and simulate complex computational models. Similar to [Simula](http://www.simula67.info/), *DE-Sim* models are implemented by defining logical process objects which read the values of a set of shared variables and schedule events to modify their values at discrete instants in time.
This website provides examples, tutorials, and documentation for *DE-Sim*.
Jonathan Karr
Arthur Goldberg
Computational biology
Mathematics
Computer science
Simulation experiment
data-driven modeling, Computational modelling, discrete-event simulation, DES, object-oriented programming, Python, data visualization, Data Science
computational scientists
Computational biologists
bioinformaticians
software engineers
programmers
BioSimulations tutorial and help
BioSimulations is a web application for sharing and re-using biomodels, simulations, and visualizations of simulations results. BioSimulations supports a wide range of modeling frameworks (e.g., kinetic, constraint-based, and logical modeling), model formats (e.g., BNGL, CellML, SBML), and...
Scientific topics: Simulation experiment, Systems biology, Computational biology
Operations: Modelling and simulation, Visualisation
Keywords: SystemsBiology, ComputationalBiology, Computational modelling, Modeling, Biomodelling, Model, Kinetic modeling, SED-ML, COMBINE
Resource type: Documentation
BioSimulations tutorial and help
https://www.biosimulations.org/about/help
http://tess.elixir-uk.org/materials/biosimulations-help
BioSimulations is a web application for sharing and re-using biomodels, simulations, and visualizations of simulations results. BioSimulations supports a wide range of modeling frameworks (e.g., kinetic, constraint-based, and logical modeling), model formats (e.g., BNGL, CellML, SBML), and simulation tools (e.g., COPASI, libRoadRunner/tellurium, NFSim, VCell). BioSimulations aims to help researchers discover published models that might be useful for their research and quickly try them via a simple web-based interface.
Jonathan Karr
Bilal Shaikh
Simulation experiment
Systems biology
Computational biology
SystemsBiology, ComputationalBiology, Computational modelling, Modeling, Biomodelling, Model, Kinetic modeling, SED-ML, COMBINE
Life Science Researchers
Computational biologists
modelers