Current Progress in Static and Dynamic Modeling of Biological Networks

  • Bernie J. DaigleJr
  • Balaji S. Srinivasan
  • Jason A. Flannick
  • Antal F. Novak
  • Serafim Batzoglou
Part of the Systems Biology book series (SYSTBIOL)


The relentless advance of biochemistry has enabled us to take apart biological systems with ever more fine-grained and precise instruments. The fruits of this dissection are millions of measurements of base pairs and biochemical concentrations. Yet to make sense of these numbers, we need to reverse our dissection by putting the system back together on the computer. This first step in this process is reconstructing molecular anatomy through static modeling, the determination of which pieces (DNA, RNA, protein, and metabolite) is present, and how they are related (e.g., regulator, target, inhibitor, cofactor). Given this broad outline of component connectivity, we may then attempt to reconstruct molecular physiology via dynamic modeling, computer simulations that model when cellular events occur (ODE), where they occur (PDE), and how frequently they recur (SDE). In this review we discuss techniques for both of these modeling paradigms, illustrating each by reference to important recent papers.


Biological networks Computer simulation Dynamic modeling Static modeling 



We thank Russ Altman for helpful discussions.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Bernie J. DaigleJr
    • 1
  • Balaji S. Srinivasan
    • 2
  • Jason A. Flannick
    • 3
  • Antal F. Novak
    • 4
  • Serafim Batzoglou
    • 4
  1. 1.Department of GeneticsStanford University School of MedicineStanfordUSA
  2. 2.Departments of Computer Science and StatisticsStanford UniversityStanfordUSA
  3. 3.Medical and Population GeneticsThe Broad Institute of Harvard and MITCambridgeUSA
  4. 4.Department of Computer ScienceStanford UniversityStanfordUSA

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