# Neural networks consisting of DNA

arXiv: https://arxiv.org/abs/2501.03235 · HTML: https://mlsanity.com/paper/2501.03235/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 34 references that are in the map.
- First posted on arXiv 12 Dec 2024.

## Builds on (most cited first, 3 of 3)

- [DNA Reservoir Computing: A Novel Molecular Computing Approach](https://mlsanity.com/paper/1306.5998/) (2013)
- [Pattern recognition in the nucleation kinetics of non-equilibrium self-assembly](https://mlsanity.com/paper/2207.06399/) (2022)
- [Interpretable machine learning of amino acid patterns in proteins: a statistical ensemble approach](https://mlsanity.com/paper/2303.15228/) (2023)

## Abstract (arXiv)

Neural networks based on soft and biological matter constitute an interesting potential alternative to traditional implementations based on electric circuits. DNA is a particularly promising system in this context due its natural ability to store information. In recent years, researchers have started to construct neural networks that are based on DNA. In this chapter, I provide a very basic introduction to the concept of DNA neural networks, aiming at an audience that is not familiar with biochemistry.