COMPUTER ANALYSIS OF LOW-COMPLEXITY AMINO ACID AND NUCLEOTIDE SEQUENCES

该项目的目标是定义、分类和 使用计算分析来分析蛋白质片段 和显示组成偏差的核苷酸序列，或 成分复杂性低得不可思议。 的蛋白质 序列，这些包括丰富的残基簇 主要是一种或几种氨基酸类型，其通常 含有这些的均聚物的片段或镶嵌物，非周期性的 低周期重复的模式和部分。 其他常见 实例包括长的非肾小球结构域。 的 在氨基酸和氨基酸序列中的偏向片段的丰度 已经确定了核苷酸序列数据库， 他们的财产与 生物功能。 局部成分的不同形式定义 复杂性被用来进行公正的鉴定， 低复杂度的部分，在不同的严格程度。 算法被改进为（a）选择片段以用于进一步的 研究，（B）在 数据库搜索，以及c）发现和分析 这种成分偏差存在于 而不是连续残基。 自动化的新方法 低复杂度序列的分类与邻近 已经被开发出来了。 B。 生物学特性：约25% 在蛋白质数据库中， 偏置段（包括一些已知的长非球形 大约55%的蛋白质含有一个或多个区域， 更多这样的片段 散布低复杂度序列 在许多环节中特别丰富。 穿插 低复杂度序列对于许多 真核生物蛋白质在形态发生和胚胎发育中起关键作用 发育，RNA加工，转录调控， 信号转导和细胞和 细胞外结构完整性 有限的结构 低复杂度区域的可用信息 蛋白质表明它们通常是非球形的， 多态的或移动的。 该项目突出了高丰度和 低复杂性蛋白质片段的生物学重要性。 对它们的分子结构和动力学的了解 开始出现在少数情况下，但这些都是一个 少数 这是未来研究的优先领域。 近年来发展起来的核苷酸分析方法 序列揭示了许多新的和复杂的 组成特征。 这些方法在以下方面很有价值： 消除了序列数据库搜索中的许多伪像 和对齐分析。

The goal of this project is to define, classify and analyze, using computational analysis, segments of protein and nucleotide sequences showing compositional bias or improbably low compositional complexity. In protein sequences, these include the abundant residue clusters of predominantly one or a few amino acid types, which commonly contain homopolymeric tracts or mosaics of these, aperiodic patterns and sections of low-period repeats. Other common examples include long non-glomerular domains. The abundance of biased segments in both amino acid and nucleotide sequence databases has been determined, and their properties are being related to evidence of biological functions. Different formal definitions of local compositional complexity were used to make unbiased identification of low-complexity segments, at different levels of stringency. Algorithms were refined to (a) select segments for further study, (b) filter out non-informative segments prior to database searches, and c) discover and analyze regions in which compositional bias is present in periodically-spaced rather than contiguous residues. New methods for automated classification and neighboring of low-complexity sequences have been developed. B. Abundance and biological properties: Approximately 25% of the residues in protein databases are in compositionally biased segments (including some known long non-globular regions) and approximately 55% of proteins contain one or more such segments. Interspersed low-complexity sequences are particularly abundant in many segments. Interspersed low-complexity sequences are particularly abundant to many eukaryotic proteins crucial in morphogenesis and embryonic development, RNA processing, transcriptional regulation, signal transduction and aspects of cellular and extracellular structural integrity. The limited structural information available for low-complexity regions of proteins indicates that they are generally non-globular and polymorphic or mobile. The project is highlighting the high abundance and biological importance of low-complexity protein segments. Knowledge of their molecular structure and dynamics is beginning to emerge in a few cases, but these are a minority. This is a priority area for future research. The methods recently developed to analyze nucleotide sequences are revealing many new and intricate compositional features. These methods are valuable in eliminating many artifacts in sequence database searches and alignment analysis.