Center for Therapeutic Innovation and Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, 1120 NW 14th St., Miami, FL, USA 33136.
Brief Bioinform. 2018 May 1;19(3):537-543. doi: 10.1093/bib/bbw130.
We present a rationale for expanding the presence of the Lisp family of programming languages in bioinformatics and computational biology research. Put simply, Lisp-family languages enable programmers to more quickly write programs that run faster than in other languages. Languages such as Common Lisp, Scheme and Clojure facilitate the creation of powerful and flexible software that is required for complex and rapidly evolving domains like biology. We will point out several important key features that distinguish languages of the Lisp family from other programming languages, and we will explain how these features can aid researchers in becoming more productive and creating better code. We will also show how these features make these languages ideal tools for artificial intelligence and machine learning applications. We will specifically stress the advantages of domain-specific languages (DSLs): languages that are specialized to a particular area, and thus not only facilitate easier research problem formulation, but also aid in the establishment of standards and best programming practices as applied to the specific research field at hand. DSLs are particularly easy to build in Common Lisp, the most comprehensive Lisp dialect, which is commonly referred to as the 'programmable programming language'. We are convinced that Lisp grants programmers unprecedented power to build increasingly sophisticated artificial intelligence systems that may ultimately transform machine learning and artificial intelligence research in bioinformatics and computational biology.
我们提出了在生物信息学和计算生物学研究中扩展 Lisp 系列编程语言的存在的理由。简单地说,Lisp 系列语言使程序员能够更快地编写比其他语言运行得更快的程序。像 Common Lisp、Scheme 和 Clojure 这样的语言促进了强大而灵活的软件的创建,而这些软件是生物学等复杂和快速发展的领域所必需的。我们将指出区分 Lisp 系列语言和其他编程语言的几个重要关键特性,并解释这些特性如何帮助研究人员提高生产力和编写更好的代码。我们还将展示这些特性如何使这些语言成为人工智能和机器学习应用的理想工具。我们将特别强调领域特定语言(DSL)的优势:专门针对特定领域的语言,因此不仅便于更容易地制定研究问题的表述,而且有助于在应用于手头特定研究领域时建立标准和最佳编程实践。在最全面的 Lisp 方言 Common Lisp 中,特别容易构建 DSL,它通常被称为“可编程编程语言”。我们相信,Lisp 赋予了程序员构建越来越复杂的人工智能系统的前所未有的能力,这可能最终会改变生物信息学和计算生物学中的机器学习和人工智能研究。