# Application of Markov Structure of Genomes to Outlier Identification and Read Classification

arXiv: https://arxiv.org/abs/2112.13117 · HTML: https://mlsanity.com/paper/2112.13117/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 25 references that are in the map.
- First posted on arXiv 24 Dec 2021.

## Builds on (most cited first, 1 of 1)

- [Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning](https://mlsanity.com/paper/1712.03141/) (2017)

## Built on by (most cited first, 2 of 2)

- [Structure of Classifier Boundaries: Case Study for a Naive Bayes Classifier](https://mlsanity.com/paper/2212.04382/) (2022)
- [Effects of Training Data Quality on Classifier Performance](https://mlsanity.com/paper/2602.21462/) (2026)

## Abstract (arXiv)

In this paper we apply the structure of genomes as second-order Markov processes specified by the distributions of successive triplets of bases to two bioinformatics problems: identification of outliers in genome databases and read classification in metagenomics, using real coronavirus and adenovirus data.