introCSB

R shiny and markdown resources for learning Computational Systems Biology

View the Project on GitHub cakieslich/introCSB

R Resources for Learning Comptutational Systems Biology

On this page you will find a variety of resources for teaching/learning Computational Systems Biology that have been developed using the R statistical language. These resources include interactive modules that are generally applicable to learning the basics of systems biology modeling, as well as, coding examples for using R to develop and analyze various types of systems biology models. The coding examples also include R shiny examples, which provide a template for developing interactive interfaces for systems biology models. Source codes for all interfaces and coding examples are also available. An interactive slide deck, also developed with R shiny, that was presented at FOSBE 2022 in a session on Systems Biology Eucation are available here.

Schematic of available R resources. Schematic overview of resources in the introCSB repository.

R Shiny Interactive Modules

This is a series of modules that are intended to provide simple interfaces to example systems models and to provide extra practice problems and are intended as a supplement the textbook: A First Course in Systems Biology . The textbook is not needed to be able to use these applications, but may be useful for further explanation.

  1. Intro to Modeling (SIR Models): Provides interfaces to selected examples from Chapter 2: Introduction to Mathematical Modeling of A First Course in Systems Biology. The expected outcomes of this module are (i) learn the parts of a model and (ii) practice predicting how perturbations to model inputs and parameters affect the model response. (Source)
  2. Static Network Models: Provides interfaces to example static network models in line with Chapter 3: Static Network Models of A First Course in Systems Biology. The expected outcomes of this module are (i) learn the basics of working with graphs; (ii) practice computing statistics based on graphs; (iii) practice using stoichiometric network models. (Source)
  3. Discrete, Recursive Models: Provides interfaces to example discrete and recursive models, including examples from Chapter 4: The Mathematics of Biological Systems of A First Course in Systems Biology. The expected outcomes of this module are (i) learn the basic principles of discrete, recursive models; (ii) explore examples of dynamic discrete recrusive models; (iii) practice generating Markov matrices. (Source)
  4. Continuous Dynamic Models: Provides interfaces to example models based on the canonical models described in pg. 102-105 of Chapter 4: The Mathematics of Biological Systems of A First Course in Systems Biology. The expected outcomes of this module are to learn the basic structure of (i) linear, (ii) Lotka-Voltera, (iii) mass action, and (iv) S-system models. (Source)
  5. Analysis of Dynamic Models: Provides interfaces to example models described in Chapter 4: The Mathematics of Biological Systems of A First Course in Systems Biology. The expected outcomes of this module are to learn the fundamentals of stability analysis including: (i) linearization of nonlinear models, (ii) eigenvalue analysis. (Source)

R Coding Examples by Topic

Below is a list of links to HTML pages with coding examples for a range of topics related to developing and analysiing systems biology models. The examples cover developing systems diagrams and developing/analyzing ODE-based systems models.

  1. Intro to Modeling
  2. Properties of Undirected Graphs
  3. Properties of Directed Graphs
  4. Discrete, Recursive Models
  5. Markov Models
  6. Parameter Estimation
  7. Stability of Linear Models
  8. Approximation of Nonlinear Models
  9. Stability of Lotka-Volterra Models
  10. Stability of S-system Models
  11. Nullcline Analysis
  12. Analyzing Hysteresis

R shiny Examples

shiny is an R package that enables the efficient development of web-based applications. The following examples demonstrate how R shiny can be used for developing interactive interfaces for systems biology models.

  1. Interface for ODE based model: Simple example of how to use R shiny to develop interactive interfaces for ODE-based models. (Demo)
  2. Interface for ODE based model with report export: Advanced example of how to use R shiny to develop interactive interfaces for ODE-based models. Includes the ability to export analysis from the model using an R markdown derived report in PDF format. (Demo)

Miscellaneous R shiny Applications

In addition to the interactive modules and the R shiny examples above, here is a list of miscellaneous applications for dynamic systems modeling.

  1. Simple interfaces to example dynamic systems.
  2. Series applications related to stability analysis of linear systems.
  3. Practice problems for stability analysis of Lotka-Volterra (predator-prey) systems.
  4. Practice problems for nullcline analysis of Lotka-Volterra (predator-prey) systems.
  5. Practice problems for stability analysis of S-systems.
  6. Practice problems for building Markov matrices from directed graphs.

Citation: Voit, E.O.: A First Course in Systems Biology. Garland Science, New York, NY, 2017, 2nd edition