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David Martinez

PhD student

Publications

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 Continue to DOI
Laura Tarnawski, Vladimir S. Shavva, Eric J. Kort, Zhengbing Zhuge, Ingrid Nilsson, Alessandro L. Gallina, David Martínez-Enguita, Benjamin Heller Sahlgren, Matthew Weiland, April S. Caravaca, Staffan Schmidt, Ping Chen, Katarina Abbas, Fu-Hua Wang, Osman Ahmed, Michael Eberhardson, Anna Farnert, Eddie Weitzberg, Mika Gustafsson, Jan Kehr, Stephen G. Malin, Henrik Hult, Mattias Carlstrom, Stefan Jovinge, Peder S. Olofsson (2023) Cholinergic regulation of vascular endothelial function by human ChAT(+) T cells Proceedings of the National Academy of Sciences of the United States of America, Vol. 120, Article e2212476120 Continue to DOI

2021

Johanna Huoman, David Martinez-Enguita, Elin Olsson, Jan Ernerudh, Lennart Nilsson, Karel Duchén, Mika Gustafsson, Maria Jenmalm (2021) Combined prenatal Lactobacillus reuteri and omega-3 supplementation synergistically modulates DNA methylation in neonatal T helper cells Clinical Epigenetics, Vol. 13, Article 135 Continue to DOI
Tejaswi Badam, Hendrik Arnold de Weerd, David Martinez, Tomas Olsson, Lars Alfredsson, Ingrid Kockum, Maja Jagodic, Zelmina Lubovac-Pilav, Mika Gustafsson (2021) A validated generally applicable approach using the systematic assessment of disease modules by GWAS reveals a multi-omic module strongly associated with risk factors in multiple sclerosis BMC Genomics, Vol. 22, Article 631 Continue to DOI

2020

Hendrik Arnold de Weerd, Tejaswi Badam, David Martinez, Julia Akesson, Daniel Muthas, Mika Gustafsson, Zelmina Lubovac-Pilav (2020) MODifieR: an Ensemble R Package for Inference of Disease Modules from Transcriptomics Networks Bioinformatics, Vol. 36, p. 3918-3919 Continue to DOI

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.

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