2016/08/08 by Bohdan B. Khomtchouk, Edmund Weitz, Claes Wahlestedt +1 · 2 voices · 3 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Earth and Planetary Sciences · #Biomedical Text Mining and Ontologies #Common Lisp #Comparison of multi-paradigm programming languages #Environmental Monitoring and Data Management #Field (mathematics) #Fifth-generation programming language #Gene Regulatory Network Analysis #Lisp #Programming paradigm #Scheme (mathematics) #Second-generation programming language #Third-generation programming language #cs.SE #q-bio.OT
paper · pdf · open access · doi:10.1093/bib/bbw130
published in Briefings in Bioinformatics 19(3), bbw130 (Oxford University Press) · 9 pages
openalex created_date 2016/08/23 · arxiv created 2016/09/19 · openalex publication_date 2016/11/22 · arxiv updated 2021/02/03 · openalex updated_date 2026/08/05
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.