Global View of Bionetwork Dynamics: Adaptive Landscape

Abstract

Quantifying the adaptive landscape in a given dynamical processes has been one of most important goals in theoretical biology. It can have immediate implications for many dynamical properties, such as robustness and plasticity. Based on recent work here I give a nontechnical brief review of this powerful quantitative concept in biology. This concept was initially proposed by S Wright 70 years ago, re-introduced by one of the founders of molecular biology and by others in different biological contexts. It was apparently forgotten by mainstream modern biologists for many years. Currently, this concept has found its increasingly important role in the development of systems biology and the modeling of bionetwork dynamics, from phage lambda genetic switch to endogenous network of cancer genesis and progression. It is an ideal quantify to describe the robustness and stability of bionetworks. I will first introduce five landmark proposals in biology on this concept, to demonstrate the important common thread in its theoretical biology development. Then I will discuss a few recent results, focusing on the work showing the logical consistency of adaptive landscape. From the perspective of a working scientist and of what needed for a dynamical theory when confronting empirical data, the adaptive landscape is useful both metaphorically and quantitatively and has captured an essential aspect of biological dynamical processes. Still, many important open problems remain to be solved. Having this important problem under control, we may expect that we are on the right road to quantitatively formulate the evolutionary dynamics discovered by Darwin and Wallace.

16 pages

References in corpus (11)

• The Yeast Cell-Cycle Network Is Robustly Designed
• Structure of Stochastic Dynamics near Fixed Points
• Stochastic Dynamical Structure (SDS) of Nonequilibrium Processes in the Absence of Detailed Balance. IV: Emerging of Stochastic Dynamical Equalities and Steady State Thermodynamics from Darwinian Dynamics
• Laws in Darwinian Evolutionary Theory
• Absolute Rate Theories of Epigenetic Stability
• Deterministic characterization of stochastic genetic circuits
• Stochastic Dynamical Structure (SDS) of Nonequilibrium Processes in the Absence of Detailed Balance. III: potential function in local stochastic dynamics and in steady state of Boltzmann-Gibbs type distribution function
• Exponential sensitivity of noise-driven switching in genetic networks
• Perfect Sampling of the Master Equation for Gene Regulatory Networks
• A Generic Rate Equation for modeling Enzymatic Reactions under Living Conditions
• Who runs fastest in an adaptive landscape: Sexual versus asexual reproduction