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An Introduction to Systems Biology by Uri Alon in 2020

systems biology, network inference, dynamical systems

Part 1. Network motifs

1. Transcription networks: basic concepts

  • 1.1 Introduction
  • 1.2 The cognitive problem of the cell
  • 1.3 Elements of transcription networks

    • 1.3.1 Separation of timescales
    • 1.3.2 The signs on the arrows: activators and repressors
    • 1.3.3 The numbers on the arrows: input functions
    • 1.3.4 Logic input functions: a simple framework for understanding network dynamics
    • 1.3.5 Multi-dimensional input functions govern genes with several inputs
  • 1.4 Dynamics and response time of simple regulation

    • 1.4.1 The response time of stable proteins is one cell generation

2. Autoregulation: a network motif

  • 2.1 Introduction
  • 2.2 Patterns, randomized networks, and network motifs
  • 2.3 Autoregulation is a network motif
  • 2.4 Negative autoregulation speeds the response time of gene circuits
  • 2.5 Negative autoregulation promotes robustness to fluctuations in production rate
  • 2.6 Summary: evolution as an engineer

    • Negative autoregulation is a network motif, a pattern that recurs throughout the network at numbers much higher than expected in random networks. To understand why negative autoregulation is a network motif, we asked what functions it can perform.
    • The second (NAR) design has the advantage that the goal, \[X_{st}\], is reached faster. Furthermore, the fluctuations around \[X_{st}\] due to variations in production and removal rate are reduced in the second, autoregulated design.
    • In an imaginary competition between two species are identical except that one uses circuit A, and the second uses circuit B, the latter would have a selective advantage. Over evolutionary times, structures that have engineering advantages would tend to be selected and appear as network motifs.

3. The feedforward loop network motif

  • 3.1 Introduction
  • 3.2 The feedforward loop is a network motif
  • 3.3 The structure of the feedforward loop gene circuit
  • 3.4 Dynamics of the coherent Type-1 FFL with AND logic
  • 3.5 The C1-FFL is a sign-sensitive delay element
  • 3.6 OR-gate C1-FFL is a sign-sensitive delay for off steps
  • 3.7 The incoherent Type-1 FFL generates pulses of output
  • 3.8 The other six FFL types can also act as filters and pulse generators
  • 3.9 Convergent evolution of FFLs
  • 3.10 Summary

4. Temporal programs and the global structure of transcription networks

  • 4.1 Introduction
  • 4.2 The single-input module (SIM) network motif
  • 4.3 The SIM can generate temporal gene expression programs
  • 4.4 The multi-output feedforward loop
  • 4.5 The multi-output FFL can generate FIFO temporal programs
  • 4.6 Signal integration by BI-FANS and dense-overlapping regulons
  • 4.7 Network motifs and the global structure of sensory transcription networks
  • 4.8 Interlocked feedforward loops in the B. subtilis sporulation network

5. Positive feedback, bistability, and memory

  • 5.1 Network motifs in developmental transcription networks
  • 5.2 Network motifs in protein-protein interaction networks

6. How to build a biological oscillator

Part 2. Robustness

7. Kinetic proofreading and conformational proofreading

8. Robust signaling by bifunctional components

9. Robustness in bacterial chemotaxis

10. Fold-change detection

11. Dynamical compensation and mutant resistance in tissues

12. Robust spatial patterning in development

Part 3. Optimality

13. Optimal gene circuit design

14. Multi-objective optimality in biology

15. Modularity

Appendices

A. The input functions of genes: Michaelis-Menten and Hill equations

B. Multi-dimensional input functions

C. Graph properties of transcription networks

D. Noise in gene expression