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首页> 外文期刊>Current Protein & Peptide Science >Editorial [Hot Topic: Intra- and Intermolecular Communications in Proteins (Guest Editor: Pier G. De Benedetti)]
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Editorial [Hot Topic: Intra- and Intermolecular Communications in Proteins (Guest Editor: Pier G. De Benedetti)]

机译:社论[热门话题:蛋白质内和分子间的交流(来宾编辑:Pier G. De Benedetti)]

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摘要

Information is going to replace matter and energy as the primary stuff of the universe [1]. Information will provide a new basic unifying conceptual framework for describing and predicting physical events and reality in the 21st century [1]. However biological matter, from atomistic-molecular level to organ-organism level, constitutes the most sophisticated multiscale (in space and time) media in which information is codified, stored and communicated according to multilevel networks of interacting dynamical systems (biological information processing).nnTwo of the most outstanding achievements of 20th century were the invention of computers and the birth of molecular biology. The advances made in these two fields over the past three decades have resulted not only in the generation of vast amounts of data and information, but also in a new understanding of the concept of information itself. Furthermore, modern science is unraveling the nature of information in numerous areas such as communication theory, biology, neuroscience, cognitive science, and biosemiotics, among others.nnConcurrently, computer based representations, simulations, modeling, and model-based reasoning are gaining in importance as a consequence of the increasing availability of computer power and sophisticated software for any kind of elaboration. In the concept of simulation as a model-based computational activity, the emphasis is on the generation and prediction of model behavior. Hence, simulation can be viewed as model-based knowledge-generation (computational experiments). Thus, simulation can be combined with other types of knowledge-generation techniques such as statistical elaboration, hypothesisprocessing and quantitative networks modeling with the aim of integrating the astonishing amount of the available biological data in a systems biology perspective.nnIn the 20th century biologists successfully explained key functions and processes essential to the functioning of living beings, in terms of physical and chemical mechanisms ultimately driven by thermodynamic laws. These laws can be considered as universal constraints on the behavior of everything existing in the natural world. These restrictions are governed by two facts: in all natural processes energy is conserved and continuously degraded through the irreversible increase of entropy. The concepts and experimental methods of biochemistry and molecular biology succeeded in disclosing, in particular, numerous pathways and complex chains of chemical reactions involved in the metabolism and growth of cells and organisms. Many structural sequences of biomolecules have been mapped out in astonishing detail and have contributed to the relevant advances of current medicine and pharmacology. The main protagonists in these complicated series of events are the proteins. From a fixed repertoire of 20 amino acids, cells can manufacture an unlimited variety of proteins, with radically different shapes and properties, which govern molecular communication and information transfer. In this respect, the following definition of information due to von Baeyer [1] is particularly appropriate: “the word information derives from the Latin Informare (in+formare), meaning to give form, shape, or character to. It is therefore to be the formative principle of or to imbue with some specific character or quality”.
机译:信息将取代物质和能量,成为宇宙的主要内容[1]。信息将为描述和预测21世纪的物理事件和现实提供一个新的基本的统一概念框架[1]。然而,从原子-分子水平到器官-有机体水平的生物物质,构成了最复杂的多尺度(时空)介质,根据相互作用的动力学系统(生物信息处理)的多层网络对信息进行编码,存储和传递。 nn 20世纪最杰出的两项成就是计算机的发明和分子生物学的诞生。在过去的三十年中,这两个领域取得的进步不仅导致产生了大量的数据和信息,而且对信息本身的概念有了新的认识。此外,现代科学正在传播理论,生物学,神经科学,认知科学和生物符号学等众多领域揭示信息的本质.nn同时,基于计算机的表示,模拟,建模和基于模型的推理正变得越来越重要。由于各种功能的计算机功能和复杂软件的可用性不断提高。在模拟作为基于模型的计算活动的概念中,重点在于模型行为的生成和预测。因此,模拟可以看作是基于模型的知识生成(计算实验)。因此,模拟可以与其他类型的知识生成技术相结合,例如统计精细化,假​​设处理和定量网络建模,目的是在系统生物学的角度整合惊人数量的可用生物数据。nn在20世纪,生物学家成功地解释了就最终由热力学定律驱动的物理和化学机制而言,对生物功能至关重要的关键功能和过程。这些定律可被视为对自然世界中所有事物行为的普遍约束。这些限制由两个事实控制:在所有自然过程中,能量都是守恒的,并且由于熵的不可逆增加而不断退化。生物化学和分子生物学的概念和实验方法成功地揭示了涉及细胞和生物体代谢和生长的化学反应的众多途径和复杂链。生物分子的许多结构序列已被详细地绘制出来,并为当前医学和药理学的相关进展做出了贡献。这些复杂事件中的主要主角是蛋白质。从固定的20个氨基酸组成的细胞库中,细胞可以制造出种类繁多的蛋白质,它们的形状和特性完全不同,它们可以控制分子的通讯和信息传递。在这方面,由冯·拜尔[1]提出的以下信息定义特别合适:“信息一词源自拉丁语信息(in + formare),意为赋予形式,形状或特征。因此,这应成为某种特定特征或品质的形成原则或使其具有吸引力”。

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