Bioinformatics and Classical Literary Study

This paper describes a collaborative project between classicists, quantitative biologists, and computer scientists to apply ideas and methods drawn from the sciences to the study of literature. A core goal of the project is the use of computational biology, natural language processing, and machine learning techniques to investigate intertextuality, reception, and related phenomena of literary significance. As a case study in our approach, here we describe the use of sequence alignment, a common technique in genomics, to detect intertextuality in Latin literature. Sequence alignment is distinguished by its ability to find inexact verbal parallels, which makes it ideal for identifying phonetic resemblances in large corpora of Latin texts. Although especially suited to Latin, sequence alignment in principle can be extended to many other languages.