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We address the need for expanding the presence of the Lisp family ofprogramming languages in bioinformatics and computational biology research.Languages of this family, like Common Lisp, Scheme, or Clojure, facilitate thecreation of powerful and flexible software models that are required for complexand rapidly evolving domains like biology. We will point out several importantkey features that distinguish languages of the Lisp family from otherprogramming languages and we will explain how these features can aidresearchers in becoming more productive and creating better code. We will alsoshow how these features make these languages ideal tools for artificialintelligence and machine learning applications. We will specifically stress theadvantages of domain-specific languages (DSL): languages which are specializedto a particular area and thus not only facilitate easier research problemformulation, but also aid in the establishment of standards and bestprogramming practices as applied to the specific research field at hand. DSLsare particularly easy to build in Common Lisp, the most comprehensive Lispdialect, which is commonly referred to as the "programmable programminglanguage." We are convinced that Lisp grants programmers unprecedented power tobuild increasingly sophisticated artificial intelligence systems that mayultimately transform machine learning and AI research in bioinformatics andcomputational biology.

The Machine that Builds Itself: How the Strengths of Lisp Family Languages Facilitate Building Complex and Flexible Bioinformatic Models