arXiv subjects

L. Hood

Publications and source records attributed to L. Hood.

4 recordsLinked to original sources

arXiv2007

Cancer Genesis and Progression as Dynamics in Functional Landscape of Endogenous Molecular-Cellular Network

An endogenous molecular-cellular network for both normal and abnormal functions is assumed to exist. This endogenous network forms a nonlinear stochastic dynamical system, with many stable attractors in its functional landscape. Normal or abnormal robust states can be decided by this network in a manner similar to the neural network. In this context cancer is hypothesized as one of its robust intrinsic states. This hypothesis implies that a nonlinear stochastic mathematical cancer model is constructible based on available experimental data and its quantitative prediction is directly testable. Within such model the genesis and progression of cancer may be viewed as stochastic transitions between different attractors. Thus it further suggests that progressions are not arbitrary. Other important issues on cancer, such as genetic vs epigenetics, double-edge effect, dormancy, are discussed in the light of present hypothesis. A different set of strategies for cancer prevention, cure, and care, is therefore suggested.

q-bio.SC↗

arXiv2006

Efficiency, Robustness and Stochasticity of Gene Regulatory Networks in Systems Biology: lambda Switch as a Working Example

Phage lambda is one of the most studied biological models in modern molecular biology. Over the past 50 years quantitative experimental knowledge on this biological model has been accumulated at all levels: physics, chemistry, genomics, proteomics, functions, and more. All its components have been known to a great detail. The theoretical task has been to integrate its components to make the organism working quantitatively in a harmonic manner. This would test our biological understanding and would lay a solid fundamental for further explorations and applications, an obvious goal of systems biology. One of the outstanding challenges in doing so has been the so-called stability puzzle of lambda switch: the biologically observed robustness and its difficult mathematical reconstruction based on known experimental values. In this chapter we review the recent theoretical and experimental efforts on tackling this problem. An emphasis is put on the minimum quantitative modeling where a successful numerical agreement between experiments and modeling has been achieved. A novel method tentatively named stochastic dynamical structure analysis emerged from such study is also discussed within a broad modeling perspective.

q-bio.SC↗

arXiv2004

Robustness, Stability and Efficiency of Phage lambda Gene Regulatory Network: Dynamical Structure Analysis

Based on our physical and biological studies we have recently developed a mathematical framework for the analysis of nonlnear dynamics. We call this framework the dynamical structure analysis. It has four dynamical elements: potential landscape, transverse matrix, descendant matrix, and stochastic drive. In particular, the importance and the existence of the potential landscape is emphasized. The dynamical structure analysis is illustrated in detail by the study of stability, robustness, and efficiency of the simplest gene regulatory network of phage lambda.

q-bio.MN↗

arXiv2004

Calculating Biological Behaviors of Epigenetic States in Phage lambda Life Cycle

Gene regulatory network of lambda phage is one the best studied model systems in molecular biology. More 50 years of experimental study has provided a tremendous amount of data at all levels: physics, chemistry, DNA, protein, and function. However, its stability and robustness for both wild type and mutants has been a notorious theoretical/mathematical problem. In this paper we report our successful calculation on the properties of this gene regulatory network. We believe it is of its first kind. Our success is of course built upon numerous previous theoretical attempts, but following 3 features make our modeling uniqu: 1) A new modeling method particular suitable for stability and robustness study; 2) Paying a close attention to the well-known difference of in vivo and in vitro; 3) Allowing more important role for noise and stochastic effect to play. The last two points have been discussed by two of us (Ao and Yin, cond-mat/0307747), which we believe would be enough to make some of previous theoretical attempts successful, too. We hope the present work would stimulate a further interest in the emerging field of gene regulatory network.

q-bio.MN↗