  We address the need for expanding the presence of the Lisp family of
programming languages in bioinformatics and computational biology research.
Languages of this family, like Common Lisp, Scheme, or Clojure, facilitate the
creation of powerful and flexible software models that are 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 (DSL): languages which 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 AI research in bioinformatics and
computational biology.
