David Martinez Enguita

Principal Research Engineer

Publications

2025

David Martínez Enguita (2025)

Explainable deep learning for DNA methylation analysis in health and disease (Doctoral thesis, comprehensive summary)

https://dx.doi.org/10.3384/9789181183320

David Martinez, Thomas Hillerton, Julia Åkesson, Daniel Kling, Maria Lerm, Mika Gustafsson (2025)

Precise and interpretable neural networks reveal epigenetic signatures of aging across youth in health and disease Frontiers in Aging, Vol. 5, Article 1526146 (Article in journal)

https://dx.doi.org/10.3389/fragi.2024.1526146

Lovisa Karlsson, Isabelle Öhrnberg, Shumaila Sayyab, David Martinez, Mika Gustafsson, Patricia Espinoza, Melissa Mendez-Aranda, Cesar Ugarte-Gil, Lameck Diero, Ronald Tonui, Jakob Paues, Maria Lerm (2025)

A DNA Methylation Signature From Buccal Swabs to Identify Tuberculosis Infection Journal of Infectious Diseases, Vol. 231, p. e47-e58 (Article in journal)

https://dx.doi.org/10.1093/infdis/jiae333

2024

Isabelle Öhrnberg, Lovisa Karlsson, Shumaila Sayyab, Jakob Paues, David Martinez, Mika Gustafsson, Patricia Espinoza-Lopez, Melissa Mendez-Aranda, Ericka Meza, Cesar Ugarte-Gil, Nicholas Kiprotich, Lameck Diero, Ronald Tonui, Maria Lerm (2024)

A DNA methylation signature identified in the buccal mucosa reflecting active tuberculosis is changing during tuberculosis treatment Scientific Reports, Vol. 14, Article 29552 (Article in journal)

https://dx.doi.org/10.1038/s41598-024-80570-4

2023

David Martinez, Sanjiv Dwivedi, Rebecka Jornsten, Mika Gustafsson (2023)

NCAE: data-driven representations using a deep network-coherent DNA methylation autoencoder identify robust disease and risk factor signatures Briefings in Bioinformatics, Vol. 24, Article bbad293 (Article in journal)

https://dx.doi.org/10.1093/bib/bbad293

News

Mika Gustafsson and David Martinez peeking into a server rack in the data center in Kärnhuset, NSC.

A step towards AI-based precision medicine

AI which finds patterns in complex biological data could eventually contribute to the development of individually tailored healthcare. Researchers have developed an AI-based method applicable to various medical and biological issues.