Wavelet Analysis of Protein Motion.

IF 0.9 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING International Journal of Wavelets Multiresolution and Information Processing Pub Date : 2012-07-01 DOI:10.1142/S0219691312500403
Noah C Benson, Valerie Daggett
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引用次数: 11

Abstract

As high-throughput molecular dynamics simulations of proteins become more common and the databases housing the results become larger and more prevalent, more sophisticated methods to quickly and accurately mine large numbers of trajectories for relevant information will have to be developed. One such method, which is only recently gaining popularity in molecular biology, is the continuous wavelet transform, which is especially well-suited for time course data such as molecular dynamics simulations. We describe techniques for the calculation and analysis of wavelet transforms of molecular dynamics trajectories in detail and present examples of how these techniques can be useful in data mining. We demonstrate that wavelets are sensitive to structural rearrangements in proteins and that they can be used to quickly detect physically relevant events. Finally, as an example of the use of this approach, we show how wavelet data mining has led to a novel hypothesis related to the mechanism of the protein γδ resolvase.

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蛋白质运动的小波分析。
随着蛋白质的高通量分子动力学模拟变得越来越普遍,存储结果的数据库变得越来越大,越来越普遍,必须开发更复杂的方法来快速准确地挖掘大量相关信息的轨迹。其中一种方法是连续小波变换,它最近才在分子生物学中流行起来,它特别适合于时间过程数据,如分子动力学模拟。我们详细描述了分子动力学轨迹的小波变换的计算和分析技术,并举例说明了这些技术如何在数据挖掘中发挥作用。我们证明了小波对蛋白质的结构重排是敏感的,并且它们可以用来快速检测物理相关事件。最后,作为使用这种方法的一个例子,我们展示了小波数据挖掘如何导致与蛋白质γδ分解机制相关的新假设。
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来源期刊
CiteScore
2.60
自引率
7.10%
发文量
52
审稿时长
2.7 months
期刊介绍: International Journal of Wavelets, Multiresolution and Information Processing (hereafter referred to as IJWMIP) is a bi-monthly publication for theoretical and applied papers on the current state-of-the-art results of wavelet analysis, multiresolution and information processing. Papers related to the IJWMIP theme are especially solicited, including theories, methodologies, algorithms and emerging applications. Topics of interest of the IJWMIP include, but are not limited to: 1. Wavelets: Wavelets and operator theory Frame and applications Time-frequency analysis and applications Sparse representation and approximation Sampling theory and compressive sensing Wavelet based algorithms and applications 2. Multiresolution: Multiresolution analysis Multiscale approximation Multiresolution image processing and signal processing Multiresolution representations Deep learning and neural networks Machine learning theory, algorithms and applications High dimensional data analysis 3. Information Processing: Data sciences Big data and applications Information theory Information systems and technology Information security Information learning and processing Artificial intelligence and pattern recognition Image/signal processing.
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