COMPUTER ANALYSIS OF AMINO ACID AND NUCLEOTIDE SEQUENCES

这个项目的目标是用计算方法定义和分析显示组成偏向(低复杂性区域或区域)的蛋白质和核苷酸序列片段，并了解它们的结构、功能和进化意义，以及它们的 病理学。在蛋白质序列中，这些区域包含很大比例的基因组编码的氨基酸(在大多数真核生物中约为25%，大多数翻译的蛋白质序列至少包含一个这样的区域)。它们可能包含几个氨基酸的同质多聚区或镶嵌体，或者重复的模式，通常是微妙的，包括那些典型的许多非球形结构域。新的数学定义和算法正在继续开发，以对低复杂性段进行无偏见的识别，并发现和 分析这些区域与其结构、相互作用和生物学特性相关的特性 功能。穿插的低复杂性序列在许多真核蛋白质中尤其丰富，这些蛋白质在形态发生和胚胎发育、RNA加工、转录调控、信号转导以及细胞和细胞外结构完整性方面都是至关重要的。结构数据表明，低复杂性的蛋白质片段通常是非球形的或构象可移动的。然而，对这些结构域的分子结构和动力学的了解仍然非常有限，因为它们通常相对难以通过结晶学和核磁共振进行研究，而且它们在当前结构数据库中所占残基的比例不到1%。因此，数学上严格的序列分析为深入了解它们的生物学和提出需要进行实验研究的问题提供了一种主要的方法。对于核苷酸和氨基酸序列，这些方法在检测和消除序列数据库搜索中的某些伪影方面也很有价值 对齐分析。

The goal of this project is to define and analyze, using computational methods, segments of protein and nucleotide sequences showing compositional bias (low-complexity regions or domains) and to understand their structural, functional and evolutionary significance, and their pathology. In protein sequences, these regions comprise a large proportion of the genome encoded amino acids (approximately 25% in most eukaryotes,and most of the translated protein sequences contain at least one such region). They may contain homopolymeric tracts or mosaics of a few amino acids, or repeated patterns, frequently subtle, including those typical of many non-globular domains. New mathematical definitions and algorithms are continuing to be developed to make unbiased identification of low-complexity segments, and to discover and analyze properties of these regions relevant to their structures, interactions and biological functions. Interspersed low-complexity sequences are particularly abundant in many eukaryotic proteins crucial in morphogenesis and embryonic development, RNA processing, transcriptional regulation, signal transduction and aspects of cellular and extracellular structural integrity. Structural data indicate that low complexity segments of proteins are generally non-globular or conformationally mobile. However, knowledge of the molecular structures and dynamics of these domains is still very limited because they are generally relatively intractable to investigation by crystallography and NMR, and they account for less than 1% of the residues in current structural databases. Hence, mathematically rigorous sequence analysis provides a primary methodology for gaining insights into their biology, and for raising questions to be investigated expermentally. These methods are also valuable, for both nucleotide and amino acid sequences, in detecting and eliminating some artifacts in sequence database searches and alignment analysis.