# Bioinformatics and Classical Literary Study

arXiv: https://arxiv.org/abs/1602.08844 · HTML: https://mlsanity.com/paper/1602.08844/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Feb 2016.

## Built on by (most cited first, 1 of 1)

- [Modeling Narrative Structure in Latin Epic Poetry with Automatically Generated Story Grammars](https://mlsanity.com/paper/2502.12276/) (2025)

## Abstract (arXiv)

This paper describes the Quantitative Criticism Lab, a collaborative initiative 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 authorial style, intertextuality, and related phenomena of literary significance. As a case study in our approach, here we review the use of sequence alignment, a common technique in genomics and computational linguistics, to detect intertextuality in Latin literature. Sequence alignment is distinguished by its ability to find inexact verbal similarities, which makes it ideal for identifying phonetic echoes in large corpora of Latin texts. Although especially suited to Latin, sequence alignment in principle can be extended to many other languages.