Reproducibiltiy of biomedical models
The center aims to enable larger and more accurate systems biology models, as well as their applications to science, bioengineering, and medicine, by enhancing their understandability, reusability, and reproducibility.
For more details on this major project please use this link
Modeling the EGF protein signaling pathway
Description - see project web site
Offical title: Reverse Sensitivity Analysis for Identifying Predictive Proteomics Signatures of Cancer
In collaboration with Steven Wiley and Wei-Jin Qian at PNNL
See home page for project for more details.
High Performance Simulation Software
Kyle: add a description followed by any links to resources
Differential Evolution Based Optimizers
Kyle, add a description here
libRoadRunner, an extensible, high-performance, cross-platform, open-source software library for the simulation and analysis of models expressed using Systems Biology Markup Language (SBML). SBML is the most widely used standard for representing dynamic networks, especially biochemical networks. libRoadRunner is fast enough to support large-scale problems such as tissue models, studies that require large numbers of repeated runs and interactive simulations. libRoadRunner is a self-contained library, able to run both as a component inside other tools via its C++ and C bindings, and interactively through its Python interface. Its Python Application Programming Interface (API) is similar to the APIs of MATLAB (www.mathworks.com) and SciPy (http://www.scipy.org/), making it fast and easy to learn. libRoadRunner uses a custom Just-In-Time (JIT) compiler built on the widely used LLVM JIT compiler framework. It compiles SBML-specified models directly into native machine code for a variety of processors, making it appropriate for solving extremely large models or repeated runs. libRoadRunner is flexible, supporting the bulk of the SBML specification (except for delay and non-linear algebraic equations) including several SBML extensions (composition and distributions). It offers multiple deterministic and stochastic integrators, as well as tools for steady-state analysis, stability analysis and structural analysis of the stoichiometric matrix.
Availability and implementation: libRoadRunner binary distributions are available for Mac OS X, Linux and Windows. The library is licensed under Apache License Version 2.0. libRoadRunner is also available for ARM-based computers such as the Raspberry Pi. http://www.libroadrunner.org provides online documentation, full build instructions, binaries and a git source repository.
Somogyi, E. T., Bouteiller, J. M., Glazier, J. A., König, M., Medley, J. K., Swat, M. H., & Sauro, H. M. (2015). libRoadRunner: a high performance SBML simulation and analysis library. Bioinformatics, 31(20), 3315-3321.
User tools for modeling and analysis of pathways.
Finding Oscillators and Bistable Switches
Biological systems can be described mathematically to model the dynamics of metabolic, protein, or gene-regulatory networks, but locating parameter regimes that induce a particular dynamic behavior can be challenging due to the vast parameter landscape, particularly in large models. In the current work, a Pythonic implementation of existing bifurcation objective functions, which reward systems that achieve a desired bifurcation behavior, is implemented to search for parameter regimes that permit oscillations or bistability. A differential evolution algorithm progressively approximates the specified bifurcation type while performing a global search of parameter space for a candidate with the best fitness. The user-friendly format facilitates integration with systems biology tools, as Python is a ubiquitous programming language. The bifurcation–evolution software is validated on published models from the BioModels Database and used to search populations of randomly-generated mass-action networks for oscillatory dynamics. Results of this search demonstrate the importance of reaction enrichment to provide flexibility and enable complex dynamic behaviors, and illustrate the role of negative feedback and time delays in generating oscillatory dynamics.
Source code: https://github.com/vporubsky/evolve-bifurcation
Tellurium is a Python-based environment for model building, simulation, and analysis that facilitates reproducibility of models in systems and synthetic biology. Tellurium is a modular, cross-platform, and open-source simulation environment composed of multiple libraries, plugins, and specialized modules and methods. Tellurium is a self-contained modeling platform which comes with a fully configured Python distribution. Two interfaces are provided, one based on the Spyder IDE which has an accessible user interface akin to MATLAB and a second based on the Jupyter Notebook, which is a format that contains live code, equations, visualizations, and narrative text. Tellurium uses libRoadRunner as the default SBML simulation engine which supports deterministic simulations, stochastic simulations, and steady-state analyses. Tellurium also includes Antimony, a human-readable model definition language which can be converted to and from SBML. Other standard Python scientific libraries such as NumPy, SciPy, and matplotlib are included by default. Additionally, we include several user-friendly plugins and advanced modules for a wide-variety of applications, ranging from complex algorithms for bifurcation analysis to multidimensional parameter scanning. By combining multiple libraries, plugins, and modules into a single package, Tellurium provides a unified but extensible solution for biological modeling and analysis for both novices and experts. Availability: tellurium.analogmachine.org.
Medley, J. Kyle, Kiri Choi, Matthias König, Lucian Smith, Stanley Gu, Joseph Hellerstein, Stuart C. Sealfon, and Herbert M. Sauro. "Tellurium notebooks—An environment for reproducible dynamical modeling in systems biology." PLoS computational biology 14, no. 6 (2018): e1006220.
Choi, Kiri, J. Kyle Medley, Matthias König, Kaylene Stocking, Lucian Smith, Stanley Gu, and Herbert M. Sauro. "Tellurium: An extensible Python-based modeling environment for systems and synthetic biology." Biosystems 171 (2018): 74-79.
Kyle/Natalis's (Part of reproducibility center)
Model Annotation Project
Prakhar/Kyle/Gennari/Nickerson (Part of reproducibility center)
descriptoin plus link to github page
Operational characteristics of cellular pathways.
The biochemical networks found in living organisms include a huge variety of control mechanisms at multiple levels of organization. While the mechanistic and molecular details of many of these control mechanisms are understood, their exact role in driving cellular behaviour is not. For example, yeast glycolysis has been studied for almost 80 years but it is only recently that we have come to understand the systemic role of the multitude of feedback and feed-forward controls that exist in this pathway.
New Modeling Approaches
Kiri Choi: Infering Kinetic Models from Perturbation Data
Inferring Reaction Networks using Perturbation Data (2018) Kiri Choi, Joesph Hellerstein, H. Steven Wiley, Herbert M. Sauro doi: https://doi.org/10.1101/351767