The layer-oriented approach to declarative languages for biological modeling.
The layer-oriented approach to declarative languages for biological modeling.
复制标题
面向层的宣言语言的方法用于生物建模。
DOI：
10.1371/journal.pcbi.1002521
复制
发表时间：
2012
影响因子：
4.3
通讯作者：
De Schutter E
中科院分区：
文献类型：
--
作者：
Raikov I;De Schutter E
我们提出了一种计算生物学建模语言的新方法，我们称之为面向层的方法。该方法源于这样的观察：许多不同的生物现象是使用一小组数学形式（例如微分方程）来描述的，而同时计算生物学的不同领域和子领域要求根据该领域公认的术语和分类来构建模型。我们的方法使用不同的语义层来表示特定领域的生物学概念和潜在的数学形式。通过添加更多层，可以将附加功能透明地添加到语言中。这种方法特别关注声明性语言，在整篇论文中我们注意到声明性方法固有的一些局限性。面向层的方法是一种明确指定如何将高级生物建模概念映射到计算表示的方法，同时抽象出特定编程语言和模拟环境的细节。为了说明这个过程，我们定义了一种示例语言来描述离子电流模型，并使用语义转换的通用数学符号来展示如何为各种仿真环境生成模型仿真代码。我们使用示例语言来描述浦肯野神经元模型，并演示如何使用面向层的方法来解决计算神经科学模型开发的几个实际问题。我们与计算生物学领域的其他建模语言工作相比，讨论了该方法的优点和局限性，并概述了可扩展、灵活的建模语言设计的一些原则。最后，我们详细描述了为我们的语言定义的语义转换。通过计算建模来理解神经功能已经产生了各种各样的软件工具，每种工具都针对特定的受众，并且通常需要以其自己独特的语言进行输入。因此，理解和交流神经科学模型是一项困难且耗时的任务。在本文中，我们提出了一种设计生物建模语言的新方法，我们称之为面向层的方法。该方法源于观察到不同的生物现象是使用一小组数学形式（例如微分方程）来描述的，这些数学形式是根据一些生物学原理构建的。我们的建议通过用于描述离子电流计算模型的计算机语言来说明。该语言由表达数学方程的规则以及根据神经科学家使用的特定术语组织这些方程的规则组成。面向层的方法有两个主要优点。首先，它允许灵活地使用数学方程来表示许多不同种类的生物模型。其次，它将语言限制在生物学概念的框架内，以便可以重用现有的建模软件。面向层的方法的目标是帮助定义计算生物学的适当符号，同时实现生物建模软件的互操作性。
We present a new approach to modeling languages for computational biology, which we call the layer-oriented approach. The approach stems from the observation that many diverse biological phenomena are described using a small set of mathematical formalisms (e.g. differential equations), while at the same time different domains and subdomains of computational biology require that models are structured according to the accepted terminology and classification of that domain. Our approach uses distinct semantic layers to represent the domain-specific biological concepts and the underlying mathematical formalisms. Additional functionality can be transparently added to the language by adding more layers. This approach is specifically concerned with declarative languages, and throughout the paper we note some of the limitations inherent to declarative approaches. The layer-oriented approach is a way to specify explicitly how high-level biological modeling concepts are mapped to a computational representation, while abstracting away details of particular programming languages and simulation environments. To illustrate this process, we define an example language for describing models of ionic currents, and use a general mathematical notation for semantic transformations to show how to generate model simulation code for various simulation environments. We use the example language to describe a Purkinje neuron model and demonstrate how the layer-oriented approach can be used for solving several practical issues of computational neuroscience model development. We discuss the advantages and limitations of the approach in comparison with other modeling language efforts in the domain of computational biology and outline some principles for extensible, flexible modeling language design. We conclude by describing in detail the semantic transformations defined for our language. The pursuit for understanding of neural function by computational modeling has produced a variety of software tools, with each tool targeting specific audiences and often requiring input in its own distinct language. Consequently, comprehending and communicating neuroscience models is a difficult and time-consuming task. In this paper we suggest a new approach towards designing biological modeling languages, which we call the layer-oriented approach. The approach stems from the observation that diverse biological phenomena are described using a small set of mathematical formalisms (e.g. differential equations), which are structured according to some biological principles. Our proposal is illustrated by means of a computer language for describing computational models of ionic currents. The language consists of rules for expressing mathematical equations as well as rules to organize these equations according to the specific terminology used by neuroscientists. The layer-oriented approach offers two chief advantages. First, it allows the flexible use of mathematical equations to represent many different kinds of biological models. Second, it restricts the language within a framework of biological concepts so that existing modeling software can be reused. The goal of the layer-oriented approach is to help define appropriate notations for computational biology while enabling interoperability of software for biological modeling.
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影响因子：
3
作者：
Cannon, Robert C.;Gewaltig, Marc-Oliver;De Schutter, Erik
通讯作者：
De Schutter, Erik
DOI：
10.1049/sb:20045008
发表时间：
2004-06-01
期刊：
Systems Biology
影响因子：
--
作者：
Hucka, M.;Finney, A.;Kitano, H.
通讯作者：
Kitano, H.
影响因子：
3
作者：
Goodman, Dan F. M.
通讯作者：
Goodman, Dan F. M.
影响因子：
4.5
作者：
Gennari JH;Neal ML;Galdzicki M;Cook DL
通讯作者：
Cook DL
影响因子：
4.3
作者：
Cannon, Robert C.;O'Donnell, Cian;Nolan, Matthew F.
通讯作者：
Nolan, Matthew F.