Theoretical Condensed Matter Physics

这笔赠款由材料研究、分子和细胞生物学以及物理系共同资助。这笔拨款支持生物物理学的理论研究。生物学中的许多问题都有一个涉及统计力学的组成部分，要么直接因为问题是在分子尺度上的，要么间接因为使用概率模型来解码基因组序列。RNA的内部沃森-克里克碱基配对定义了它的二级结构，比蛋白质中相应的元素更好地描绘了二级结构。最近编写了一个动力学蒙特卡罗程序来跟踪RNA二级结构的形成，长度可达~400个碱基，并包括非嵌套构型(假结)。与最近的实验一样，该密码将应用于分子的末端。蛋白质在细胞中的运输涉及许多步骤，其中蛋白质被分类和定位，例如，在高尔基体底物中，由不同的酶在连续的池中处理。与美国国立卫生研究院的一个实验室合作，将设计和测试允许高尔基酶在连接的膜系统中定位的模型。这些都是流行的想法的替代，要么底物生活在固定的隔室中，酶通过主动的分选和囊泡运输过程通过隔室流动，要么酶是固定的，底物被主动运输。现在有多种荧光蛋白可以在活细胞中表达(有时是与天然蛋白的嵌合体)，这使得可以测量它们在一个细胞中的数量作为时间的函数。与洛克菲勒的一个实验小组合作，我们正在对转录和翻译中的随机噪音(由于少量分子)进行建模。更广泛地说，我们将在实验和理论上合作，以评估随机效应是否影响细菌的适应性。蛋白质与环境信号结合并整合的短基序对基因转录的调控对生物学的许多领域都很重要。一种算法已经被设计出来，它可以根据迭代构建的词典中出现的较短字符串的频率，找到不太可能的碱基字符串。当它应用于酵母时，它产生了许多重要的基序，我们打算将该算法应用于其他生物，并将其扩展到识别模糊模式。近缘物种的比较是恢复调控基序的另一种方式，我们打算应用概率比对编码来适应非编码序列中的进化速度，并将概率分配给比机会更保守的区域，从而实现功能。一种将基因表达数据直接与序列相关联并赋予统计学意义的算法已经在酵母上进行了试验，并将推广到其他多细胞生物体。这项拨款由材料研究、分子和细胞生物学以及物理系共同资助。这笔拨款支持生物物理学的理论研究。生物学中的许多问题都有一个涉及统计力学的组成部分，要么直接因为问题是在分子尺度上，要么间接因为概率模型被用来解码基因组序列。这项研究将使用理论凝聚态物理的技术来研究当前生物学感兴趣的各种问题。

This grant is co-funded by the Divisions of Materials Research, Molecular and Cellular Biology, and Physics. The grant supports theoretical research in biological physics.Many problems in biology have a component that involves statistical mechanics either directly because the question is on the molecular scale, or indirectly because a probablistic model is being used to decode a genomic sequence.The internal Watson-Crick base pairing of RNA defines its secondary structure which is better delineated energetically than the corresponding elements in proteins. A kinetic Monte Carlo code has recently been written to follow the formation of secondary structure for RNA's up to ~ 400 bases in length and includes non-nested configurations (pseudoknots). The code will be applied to the ends of the molecule as in recent experiments.Protein trafficing in cells involves numerous steps where proteins are sorted and targeted, e.g., in the Golgi substrate as processed in successive cisternae by different enzymes. In collaboration with a laboratory at NIH, models which allow for Golgi enzyme localization in a connected membrane system will be devised and tested. These are alternatives to the prevailing ideas that either the substrate lives in fixed compartments and the enzymes flux through the compartments via an active process of sorting and vesicle transport, or the enzymes are fixed and the substrates are actively transported.There are now multiple fluorescent proteins that can be expressed in live cells (sometimes as chimeras with native proteins), which allow for measurement of their number in one cell as a function of time. In conjunction with an experimental group at Rockefeller, we are modeling the stochastic noise (due to a small number of molecules) in transcription and translation. More generally we will collaborate on experiments and theory to assess whether stochastic effects impact the fitness of bacteria.The regulation of gene transcription by short, e.g., 10-30 bp, motifs to which proteins bind and integrate environmental signals is important to many areas of biology. An algorithm has been devised which finds improbable strings of bases, based on the frequency of shorter strings present in an iteratively constructed 'dictionary.' It yielded many significant motifs when applied to yeast, and we intend to apply the algorithm to other organisms, as well as extend it to recognize fuzzy patterns. The comparison of related species is another way to recover regulatory motifs and we intend to apply a probablistic alignment code both to fit the evolution rate in noncoding sequence and assign probabilities to the regions which are more conserved than chance and thus functional. An algorithm to relate gene expression data directly to sequence and assign statistical significance has been tried on yeast and will be extended to other multicellualr organisms.%%%This grant is co-funded by the Divisions of Materials Research, Molecular and Cellular Biology, and Physics. The grant supports theoretical research in biological physics.Many problems in biology have a component that involves statistical mechanics either directly because the question is on the molecular scale, or indirectly because a probablistic model is being used to decode a genomic sequence. This research will investigate a variety of problems of current biological interest using techniques from theoretical condensed matter physics.***