自20世纪50年代以来，人们就已经认识到不编码蛋白质的RNA分子基因(ncRNAs)的存在，但直到最近，除了极其重要的核糖体基因和转移RNA基因外，大多数关注点都在蛋白质编码基因上。然而，从RNA执行催化功能的能力，到发现核糖体、microRNA和其他核糖调节剂在基本上所有生物体中执行关键任务，一系列长时期的惊人发现，使人们对生物圈的这一原始组成部分产生了蓬勃的兴趣。然而，RNA分子的结构特征和进化制约因素与蛋白质的结构特征和进化制约因素截然不同，因此有必要开发一套全新的信息学工具来解决这些挑战。在RNA Sequence, Structure, Function: 计算和生物信息学方法》中，该领域的专家研究人员从实用和计算/算法两个角度描述了这些方法的大量相关部分。注重这两个方向，既解决了有兴趣了解更多RNA生物信息学的生物学家，也解决了有兴趣了解更多算法细节方面的生物信息学家。本书采用非常成功的《分子生物学方法》系列格式编写，各章包括那种对获得最佳结果至关重要的详细描述和实施建议。
《RNA Sequence, Structure, Function: 计算和生物信息学方法》有助于科学家继续研究RNA生物信息学的关键方法和原理。
The existence of genes for RNA molecules not coding for proteins (ncRNAs) has been recognized since the 1950's, but until recently, aside from the critically important ribosomal and transfer RNA genes, most focus has been on protein coding genes. However, a long series of striking discoveries, from RNA's ability to carry out catalytic function, to discovery of riboswitches, microRNAs and other ribo-regulators performing critical tasks in essentially all living organisms, has created a burgeoning interest in this primordial component of the biosphere. However, the structural characteristics and evolutionary constraints on RNA molecules are very different from those of proteins, necessitating development of a completely new suite of informatic tools to address these challenges. In RNA Sequence, Structure, Function: Computational and Bioinformatic Methods, expert researchers in the field describe a substantial and relevant fraction of these methodologies from both practical and computational/algorithmic perspectives. Focusing on both of these directions addresses both the biologist interested in knowing more about RNA bioinformatics as well as the bioinformaticist interested in more detailed aspects of the algorithms. Written in the highly successful Methods in Molecular Biology series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results.
Thorough and intuitive, RNA Sequence, Structure, Function: Computational and Bioinformatic Methods aids scientists in continuing to study key methods and principles of RNA bioinformatics.
