Identification of promoter through stochastic approach

T. Jabid, F. Anwar, S. M. Baker, M. Shoyaib
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引用次数: 2

Abstract

Analysis of a gene sequence, which is transcribed into RNA and then translated into protein, is a difficult task. If this could be achieved, it would make possible better understand how the organisms are developed from DNA information. The behavior of gene is highly influenced by promoter sequences residing upstream or downstream of the Transcription Start Site (TSS). The promoter recognition process is a part of the complex process where genes interact with each other over time and actually regulates the whole working process of a cell. This paper attempts to develop an efficient algorithm that can successfully distinguish promoters and non promoters by analyzing statistical data. A learning model is developed from the known dataset to predict the unknown ones.
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用随机方法识别启动子
基因序列被转录成RNA,然后翻译成蛋白质,对其进行分析是一项艰巨的任务。如果能够实现这一点,就有可能更好地了解生物体是如何从DNA信息中发育出来的。基因的行为受到转录起始位点(Transcription Start Site, TSS)上游或下游启动子序列的高度影响。启动子识别过程是复杂过程的一部分,基因之间随着时间的推移相互作用,实际上调节了细胞的整个工作过程。本文试图通过对统计数据的分析,开发一种能够成功区分启动子和非启动子的有效算法。在已知数据集的基础上建立学习模型来预测未知数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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