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A Self-Adaptive Spectral Rotation Approach to Detection of DNA Sequence Periodicities and Their Relationship with Molecular Mechanisms.

机译:DNA序列周期性检测的自适应光谱旋转方法及其与分子机制的关系。

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摘要

Computational investigations into the relationship and interaction between DNA sequences and cell components help biologists and medical scientists to address many important issues. This study initiates a new approach, namely, Self-Adaptive Spectral Rotation (SASR), to investigate the relationship between periodicities in DNA sequences and various molecular mechanisms in cells. This newly developed approach could be very useful in fields of bioinformatics, including protein-coding region prediction and nucleosome positioning prediction.;Protein-coding region prediction, especially computational methods to find locations of protein-coding regions in uncharacterized DNA sequences, is a meaningful issue in computational molecular biology. In this study, the SASR approach is first developed to visualize a coding related feature, i.e., the Triplet Periodicity (TP), in DNA sequences. Applications on real genomic datasets show that, in SASR's output, the graphic patterns for coding and non-coding regions differ so significantly that the former can be visually distinguished from the latter. Such visualization by the SASR approach requires no training process, and takes the advantage of "auto-scale analysis ability" from human vision, Besides, a T-Z-T approach is developed to extract numerical information from the SASR's graphic result. The combination of the SASR and the T-Z-T provides computational predictions of coding regions without any training process.;Experimental studies on nucleosome positioning have revealed the preference of nucleosome binding for certain regions of a DNA sequence. However, it is still not clear whether such a binding preference is sequence-specific. In this study, the original SASR approach is extended to investigate the relationship between nucleosome formation and the ∼10bp periodicity of dinucleotides in DNA sequences. A Genetic Algorithm (GA) based method is developed to identify which dinucleotide combination mostly connects its ∼10bp periodicity with nucleosome formation. The results from the GA support the "sequence-specific" argument of nucleosome formation, and also imply some new principles of nucleosome formation.;Besides the TP and the ∼10bp periodicity, in this study, another extension of the SASR approach, i.e., the mature SASR, shows its ability to detect a hypothetical anti-TP property in DNA sequences. Some real DNA fragments are found with such an anti-TP property by using the mature SASR.
机译:对DNA序列与细胞成分之间的关​​系和相互作用的计算研究有助于生物学家和医学科学家解决许多重要问题。这项研究开创了一种新方法,即自适应光谱旋转(SASR),以研究DNA序列的周期性与细胞中各种分子机制之间的关系。这种新开发的方法在生物信息学领域可能非常有用,包括蛋白质编码区预测和核小体定位预测。蛋白质编码区预测,特别是在未表征的DNA序列中找到蛋白质编码区位置的计算方法,是有意义的计算分子生物学中的问题。在这项研究中,首先开发出SASR方法以可视化DNA序列中与编码相关的特征,即Triplet Periodicity(TP)。实际基因组数据集上的应用表明,在SASR的输出中,编码区域和非编码区域的图形模式差异很大,因此可以从视觉上区分前者和后者。通过SASR方法进行的这种可视化不需要任何培训过程,并且利用了人类视觉的“自动缩放分析能力”。此外,还开发了一种T-Z-T方法来从SASR的图形结果中提取数字信息。 SASR和T-Z-T的结合提供了对编码区域的计算预测,而无需任何训练过程。核小体定位的实验研究表明,核小体结合对于DNA序列某些区域的偏好。然而,仍然不清楚这种结合偏好是否是序列特异性的。在这项研究中,扩展了最初的SASR方法以研究核小体形成与DNA序列中双核苷酸的〜10bp周期性之间的关系。开发了一种基于遗传算法(GA)的方法,以识别哪种双核苷酸组合主要将其约10bp的周期性与核小体形成联系起来。 GA的结果支持核小体形成的“序列特异性”论点,也暗示了核小体形成的一些新原理。除TP和约10bp的周期性外,本研究还对SASR方法进行了另一种扩展,即成熟的SASR显示了其检测DNA序列中假设的抗TP特性的能力。通过使用成熟的SASR,发现了一些具有这种抗TP特性的真实DNA片段。

著录项

  • 作者

    Chen, Bo.;

  • 作者单位

    Hong Kong Polytechnic University (Hong Kong).;

  • 授予单位 Hong Kong Polytechnic University (Hong Kong).;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 189 p.
  • 总页数 189
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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