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第二定律与生物物理学

The Second Law and Biophysics
课程网址: http://videolectures.net/mitworld_dill_slb/  
主讲教师: Kenneth Dill
开课单位: 加利福尼亚大学
开课时间: 2013-07-24
课程语种: 英语
中文简介:
“生物学很混乱,”肯尼思·迪尔说,“它主要是关于熵。”只要看看生物系统如何在每一个可能的转折处重复熵:一个母细胞制造两个子细胞,每个细胞分配一个DNA分子;和生化反应的过程,水从分子上剥离。 Dill确信“未来的生物学语言将是非平衡统计力学。”他正在进行实验,探索动力学规律如何应用于非常小的生物系统,例如细胞内部。传统的宏观动态,Dill解释说,浓度梯度或温度梯度驱动通量的定律。但在细胞内部,有些元素有时含有五个分子,然后在下一个瞬间,有500个分子。问题是如何在动态方面考虑这些高度波动的数量。为此,研究人员一直在设计实验来描述微系统的动力学.Dill的同事已经建立了一个微流体装置,可以绘制微观粒子随时间的扩散,可能的路径和速率。为了帮助构建这项工作,并对可比较的系统做出预测,他们使用熵的类比,描述为口径。就像可以存在最大熵一样,可以有最大口径“预测动力学定律的极值原理,就像最大熵预测平衡一样,”Dill说。这种通量建模方法可以处理粒子在特定时间段内可能出现的轨迹和速度。还将描述统计力学如何应用于“狗跳蚤模型”。科学家们计算跳蚤从一只狗跳到另一只狗的可能性,以及对抗浓度梯度。 Dill说这个模型可以用来“以最简单的方式论证扩散是如何工作的”来预测通量分布。科学家们还制定了一个模拟两个状态动力学过程的实验,例如单离子通道的开启和关闭。相邻激光阱中摆动的胶体粒子可以从一个陷阱跳到另一个陷阱,这取决于势垒的高度和井的深度。这使研究人员能够计算轨迹,并测量“完整的动态分布函数。”Dill说,最大口径方法的价值在于,您可以获得有关系统处于状态的第一时刻的数据“并且可以从中预测其他一切。“Dill说,”有一个关于极值原理和基于分区的方法的一个好处就是用常规热力学来证明各种类比。“到目前为止,研究人员只采用了最早的步骤来说明这一新的方法。 。 “口径的潜在力量尚未经过测试,”迪尔认为。
课程简介: “Biology is messy,” says Kenneth Dill, and it’s “heavily about entropy.” Just look at how biological systems repeat entropy at every possible turn: a parent cell making two daughter cells, sending one DNA molecule to each; and the process of biochemical reactions, with water getting stripped off the molecules. Dill is convinced that the “language of biology in the future will be nonequilibrium statistical mechanics.” He’s engaged in experiments that explore how dynamical laws apply to very small biological systems, such as those inside cells. Traditional macro-scale dynamics, explains Dill, have laws where concentration gradients or temperature gradients drive flux. But inside cells, there are elements that sometimes contain five molecules, and then in the next instant, 500 molecules. The question is how to think about these highly fluctuating quantities in terms of dynamics. To that end, researchers have been devising experiments to describe the dynamics of micro systems. Dill’s colleagues have built a microfluidics apparatus that plots the diffusion of microscopic particles over time, their probable routes and rates. To help frame this work, and make predictions about comparable systems, they use an analogy to entropy, described as caliber. Just as there can be maximum entropy, there can be maximum caliber -- “an extremum principle that predicts the dynamical laws, just as maximum entropy predicts equilibrium,” says Dill. This way of modeling fluxes deals with the likely trajectories and speeds traveled by particles within a certain time period. Dill also describes how statistical mechanics applies in the “dog-flea model.” Scientists calculate the probabilities of fleas jumping from one dog to another, and of going up against a concentration gradient. Dill says this model can be used “to argue in the simplest way how diffusion works,” to predict flux distribution. Scientists have also worked out an experiment to model two-state kinetic processes, such as single ion channels opening and closing. Colloidal particles wiggling in adjacent laser traps can jump over barriers from one trap to the other, depending on the height of the barrier and the depth of the well. This allows researchers to count trajectories, and to measure “the full dynamical distribution functions.” The value of the maximum caliber approach, Dill says, is that you get data about the first moment of the system in state “and from them you can predict everything else.” Says Dill, “One of the great things about having an extremum principle and partition-based approach is it turns out all kinds of analogies with normal thermodynamics.” So far, researchers have only taken the earliest steps to illustrate this new tack. “The potential power of caliber hasn’t been tested yet,” believes Dill.
关 键 词: 生物学; 重复熵; 非平衡统计力学
课程来源: 视频讲座网
最后编审: 2019-05-21:cwx
阅读次数: 87