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Systems Biology Foundations and Formalisms Training | Modeling Paradigms, Dynamics and Standards

NTHRYS >> Services >> Academic Services >> Training Programs >> Bioinformatics Training >> Systems Biology, Network Modeling & Pathway Dynamics >> Systems Biology Foundations and Formalisms Training | Modeling Paradigms, Dynamics and Standards

Systems Biology Foundations and Formalisms — Hands-on

Gain a solid foundations level understanding of systems biology as a discipline that connects genes, pathways and phenotypes through explicit models. Learn how to move from verbal mechanisms to mathematical formalisms and simulatable models that support decision making in research and development.

Systems Biology Foundations and Formalisms
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Session 1
Fee: Rs 8800
Systems Thinking and Modeling Paradigms
  • What is systems biology and why modeling is needed
  • genes to pathways to phenotypes top down vs bottom up mechanistic vs data driven
  • Modeling paradigms in systems biology
  • logical and rule based constraint based dynamic kinetic models
  • Conceptual model building
  • storyboards and causal diagrams states and flows boundary and scope
Session 2
Fee: Rs 11800
Mathematical Formulations and Dynamics
  • From reactions to equations
  • mass action kinetics Hill and Michaelis Menten forms state variables and parameters
  • Deterministic and stochastic formalisms
  • ordinary differential equations ODE stochastic differential equations SDE when noise matters
  • Simulation ready formulations
  • initial conditions time scales and units numerical solvers overview
Session 3
Fee: Rs 14800
Network Structure, Feedback and Behavior
  • From pathways to interaction networks
  • nodes and edges motifs and modules feedback and feedforward loops
  • Qualitative system behavior
  • steady states and transients switches and oscillations robustness concepts
  • Introduction to model standards
  • SBML basics SBGN and visual maps model repositories BioModels
Session 4
Fee: Rs 18800
Mini Capstone: Build a Simple Systems Model
  • Case study selection and problem framing
  • Theory plus guided practical
  • Implement a small SBML model and run simulations
  • use of open source tools parameter exploration basic sensitivity checks
  • Deliverables: model file, notebook and brief report
  • SBML model Python or R notebook PDF or HTML summary


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