Mesarovic M D, Sreenath S N, Keene J D
Systems Biology Center Initiative, Dept of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106-7071, USA.
Syst Biol (Stevenage). 2004 Jun;1(1):19-27. doi: 10.1049/sb:20045010.
Due in large measure to the explosive progress in molecular biology, biology has become arguably the most exciting scientific field. The first half of the 21st century is sometimes referred to as the 'era of biology', analogous to the first half of the 20th century, which was considered to be the 'era of physics'. Yet, biology is facing a crisis--or is it an opportunity--reminiscent of the state of biology in pre-double-helix time. The principal challenge facing systems biology is complexity. According to Hood, 'Systems biology defines and analyses the interrelationships of all of the elements in a functioning system in order to understand how the system works.' With 30000+ genes in the human genome the study of all relationships simultaneously becomes a formidably complex problem. Hanahan and Weinberg raised the question as to whether progress will consist of 'adding further layers of complexity to a scientific literature that is already complex almost beyond measure' or whether the progress will lead to a 'science with a conceptual structure and logical coherence that rivals that of chemistry or physics.' At the core of the challenge is the need for a new approach, a shift from reductionism to a holistic perspective. However, more than just a pronouncement of a new approach is needed. We suggest that what is needed is to provide a conceptual framework for systems biology research. We propose that the concept of a complex system, i.e. a system of systems as defined in mathematical general systems theory (MGST), is central to provide such a framework. We further argue that for a deeper understanding in systems biology investigations should go beyond building numerical mathematical or computer models--important as they are. Biological phenomena cannot be predicted with the level of numerical precision as in classical physics. Explanations in terms of how the categories of systems are organised to function in ever changing conditions are more revealing. Non-numerical mathematical tools are appropriate for the task. Such a categorical perspective led us to propose that the core of understanding in systems biology depends on the search for organising principles rather than solely on construction of predictive descriptions (i.e. models) that exactly outline the evolution of systems in space and time. The search for organising principles requires an identification/discovery of new concepts and hypotheses. Some of them, such as coordination motifs for transcriptional regulatory networks and bounded autonomy of levccels in a hierarchy, are outlined in this article. Experimental designs are outlined to help verify the applicability of the interaction balance principle of coordination to transcriptional and posttranscriptional networks.
在很大程度上,由于分子生物学的迅猛发展,生物学已成为最令人兴奋的科学领域。21世纪上半叶有时被称为“生物学时代”,类似于20世纪上半叶被认为是“物理学时代”。然而,生物学正面临一场危机——或者说是一个机遇——这让人想起双螺旋结构发现之前生物学的状况。系统生物学面临的主要挑战是复杂性。根据胡德的说法,“系统生物学定义并分析一个功能系统中所有元素的相互关系,以便理解系统是如何运作的。”人类基因组中有3万多个基因,同时研究所有这些关系就成为了一个极其复杂的问题。哈纳汉和温伯格提出了这样一个问题:进展是会包括“给已经几乎复杂到无法估量的科学文献再增加更多层次的复杂性”,还是进展会导向一门“具有与化学或物理学相媲美的概念结构和逻辑连贯性的科学”。挑战的核心在于需要一种新方法,即从还原论转向整体论视角。然而,仅仅宣称一种新方法是不够的。我们认为需要为系统生物学研究提供一个概念框架。我们提出,复杂系统的概念,即数学一般系统理论(MGST)中所定义的系统之系统,对于提供这样一个框架至关重要。我们进一步认为,为了在系统生物学中有更深入的理解,研究不应仅仅局限于构建数值数学模型或计算机模型——尽管它们很重要。生物现象无法像经典物理学那样以数值精度进行预测。从系统类别如何在不断变化的条件下组织起来发挥功能的角度进行解释更具启发性。非数值数学工具适合这项任务。这种分类视角促使我们提出,系统生物学理解的核心在于寻找组织原则,而不仅仅是构建精确勾勒系统在空间和时间中演化的预测性描述(即模型)。寻找组织原则需要识别/发现新的概念和假设。本文概述了其中一些概念和假设,比如转录调控网络的协调基序以及层次结构中各级的有限自主性。还概述了实验设计,以帮助验证协调的相互作用平衡原理在转录和转录后网络中的适用性。