The MEME suite of motif-based sequence analysis tools

描述(由申请人提供)：DNA和蛋白质序列将有关生物功能的信息数字化地存储在一种尚未完全理解的复杂代码中。这种密码的基本单位是序列基序，它被定义为一种小的、重复出现的DNA或蛋白质序列模式。例如，DNA基序可能参与打开或关闭基因的转录，以响应环境提示。蛋白质基序可能编码结合位点的属性，从而允许蛋白质执行其功能。基于基序分析软件的Meme Suite建立了DNA和蛋白质基序的统计模型，使生物学家能够发现新的基序，搜索已知基序的新实例，并将基序相互比较。这一提议继续开发和维护世界各地生物学家经常使用的表情包套件。这项工作的目标有五个方面：(1)增加Meme套件的可访问性、可用性和互操作性，(2)扩展Meme套件，以处理有关组蛋白修饰、甲基化、核小体定位和DNaseI超敏位点的表观遗传数据，(3)将各种现有的基于Motif的软件工具集成到Meme套件中，(4)通过已证实的改进来增强Meme套件使用的算法，以及(5)继续改进我们的用户支持服务。与公共健康相关：该项目将改进现有的、广泛使用的软件，使生物学家能够了解DNA和蛋白质序列如何编码有关生物功能的信息。识别和准确描述功能序列基序使科学家能够了解基因是如何开启和关闭的，以及蛋白质如何在细胞中执行其功能。这种知识对于细胞的基本分子机制的任何模型都是基本的，特别是对于疾病过程的分子尺度模型。

DESCRIPTION (provided by applicant): DNA and protein sequences digitally store information about biological function in a complex code that is not yet fully understood. The fundamental unit of this code is the sequence motif, which is defined as a small, recurring DNA or protein sequence pattern. A DNA motif might be involved, for example, in turning on or off the transcription of a gene in response to environmental cues. A protein motif might encode the properties of the binding site that allows the protein to carry out its function. The MEME Suite of motif-based sequence analysis software builds statistical models of DNA and protein motifs, allowing biologists to discover novel motifs, to search for new instances of known motifs, and to compare motifs to one another. This proposal continues to develop and maintain the MEME Suite, which is in regular use by biologists around the world. The aims of this work are five-fold: (1) to increase the accessibility, usability and interoperability of the MEME Suite, (2) to expand the MEME Suite to handle epigenetic data regarding histone modifications, methylation, nucleosome positioning and DNaseI hypersensitive sites, (3) to integrate a variety of existing motif-based software tools into the MEME Suite, (4) to augment the algorithms used by the MEME Suite with proven enhancements, and (5) to continue to improve our user support services. PUBLIC HEALTH RELEVANCE: This project will improve existing, widely used software that enables biologists to understand how DNA and protein sequences encode information about biological function. Identifying and accurately characterizing functional sequence motifs allows scientists to understand how genes are turned on and off and how proteins carry out their functions in the cell. Such knowledge is fundamental to any model of the basic molecular mechanisms of the cell, and in particular, for molecular-scale models of disease processes.