SEGMENTATION OF PULMONARY NODULE IMAGES USING TOTAL VARIATION MINIMIZATION

在过去的一年里，我们一直在使用统计机械 蛋白质折叠研究的分析和计算机模拟 有问题。我们的研究在识别 研究折叠问题的正确方法 了解蛋白质折叠的基本物理原理。我们进行了一次 详细分析了两种流行的统计机制 蛋白质模型。这一分析是由我们新推出的 开发了计算程序，可以准确地确定 不同蛋白质模型的态密度。这样的信息 使我们能够表征分子的热力学和折叠动力学 蛋白质的模型是定量的。我们发现，即使两个人 不同类型的模型具有相似的热力学性质，其起源 不同模型的折叠协同性不同。基于联系人的 立方晶格链模型缺乏典型的长程协同效应 在真实蛋白质中的局部结构单位之间，但另一个模型 很好地描述了这种行为。这两种类型的模型有不同 折叠动力学；它们的态密度，从而它们的能量 风景，是不同的。通过确定两者之间的差异 流行的蛋白质模型和去除非物理特征的 蛋白质折叠的理论图景，加深了我们的理解 关于蛋白质折叠的问题。我们的结果导致了更多 蛋白质协同折叠的现实分子机制， 我们得到了关于哪种折叠的更明确的信息 行为会随着某些类型的交互而产生，以及如何 将各种分子内相互作用结合成一种特定的力 折叠蛋白质的区域。我们目前正在 我们开发通用蛋白质的最新研究进展 预测自然构造的具有真实力场的模型 用于真实蛋白质的研究和设计具有新性质的新蛋白质。

During the last year, we have been using statistical-mechanical analysis and computer simulations to study the protein-folding problem. Our research made significant progress in identifying the correct approaches for studying the folding problem and in understanding the basic physics of protein folding. We carried out detailed analyses of the statistical mechanics of the two prevailing protein models. This analysis was made possible by our newly developed compuation procedures which can determine accurately the density of states of the different protein models. Such information allows us to characterize the thermodynamics and folding kinetics of the protein models quantitatively. We found that, even though the two types of models have similar thermodynamic character, the origins of folding cooperativity of the models are different. The contact-based cubic-lattice chain model lacks the typical long-range cooperativity among locally structured units in real proteins, but the other model describes such behavior well. The two types of models have different folding kinetics; their densities of states, thereby their energy landscapes, are different. By identifying the differences among two prevailing protein models and removing the unphysical features in the theoretical picture of protein folding, we sharpen our understanding about the protein folding problem. Our results lead to a more realistic molecular mechanism for the cooperative folding of proteins, and we obtain more definite information about what kind of folding behavior will arise with certain types of interactions and how to combine the various intramolecular interactions into a specific force field for folding proteins. We are currently building upon the progress of our most recent research to develop a general protein model with a realistic force field for predicting the native structure of real proteins and for designing new proteins with novel properties.