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LIKELIHOOD ALIGNMENT AND EVOLUTIONARY MODELS

LIKELIHOOD ALIGNMENT AND EVOLUTIONARY MODELS
可能性对齐和进化模型
批准号:
3308813
负责人:
Jeffrey L. Thorne
金额:
$3.4万
依托单位国家:
美国
项目类别:
财政年份:
1993
资助国家:
美国
项目状态:
已结题
起止时间:
1993-09-01 至 1995-08-31

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中文摘要
翻译
对齐是一种关于进化对应的假设, DNA或蛋白质序列。序列比对对于研究 分子进化此外,它们还可用于检测高度 保守的功能结构域,是一些策略的组成部分, 搜索序列数据库。广泛使用的对准技术依赖于 进化论的假设都是未说明和不清楚的。特设 这些技术的基础对它们产生的对齐产生了怀疑。 拟议的研究将涉及发展的方法, 基于明确进化模型的推论。 特别 将注意使这些模型尽可能真实。 核苷酸组成的区域异质性, 进化速率,以及相对普遍的长度分布, 将允许插入-删除事件。 进化模型将为以下方面提供一个基本框架: 应用包括:蛋白质二级结构的推断, 进化参数的估计,以及 可靠的区域对齐。此外,还提供了一种同时 将介绍比对多个序列和重建同源性。 从这项研究中产生的序列分析技术将全部 有一个可能性的基础,并可以利用这一事实, 统计推断的方法已被深入研究。 的 这些技术的进化观点和概率性质 应该联合收割机使它们比以前提出的更精确。
英文摘要
An alignment is a hypothesis about the evolutionary correspondence between DNA or protein sequences. Sequence alignments are crucial for the study of molecular evolution. In addition, they can be used to detect highly conserved functional domains and are a component of some strategies for searching sequence databases. Widely-used alignment techniques rely on evolutionary assumptions that are both unstated and unclear. The ad hoc basis of these techniques casts doubt on the alignments that they produce. The proposed research will involve development of methods for alignment inference that are based upon explicit evolutionary models. Special attention will be paid to making these models as realIstic as possible. Regional heterogeneity of nucleotide composition, heterogeneity of evolutionary rates, and relatively general distributions for lengths of insertion-deletion events will be allowed. The evolutionary models will provide an underlying framework for applications that include: the inference of protein secondary structure, the estimation of evolutionary parameters, and the determination of reliable regions in alignments. In addition, a method to simultaneously align multiple sequences and reconstruct phylogenies will be introduced. The sequence analysis techniques that arise from this research will all have a likelihood basis and can take advantage of the fact that likelihood approaches to statistical inference have been intensively studied. The evolutionary perspective and probabilistic nature of these techniques should combine to make them more accurate than those previously proposed.
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会议论文
Evolutionary inferences from protein-coding genes
Evolutionary inferences from protein-coding genes
Evolutionary inferences from protein-coding genes
Evolutionary inferences from protein-coding genes
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