Data-driven bioinformatics to disentangle cells within a tissue microenvironment

Jesper N Tegner; David Gomez-Cabrero

doi:10.1016/j.tcb.2022.03.009

Data-driven bioinformatics to disentangle cells within a tissue microenvironment

Trends Cell Biol. 2022 Jun;32(6):467-469. doi: 10.1016/j.tcb.2022.03.009. Epub 2022 Apr 13.

Authors

Jesper N Tegner¹, David Gomez-Cabrero²

Affiliations

¹ Bioscience Program, Bioengineering Program, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia; Computer Science Program, Statistics Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia; Unit of Computational Medicine, Department of Medicine, Center for Molecular Medicine, Karolinska Institutet, Karolinska University Hospital, L8:05, SE-171 76, Stockholm, Sweden; Science for Life Laboratory, Tomtebodavägen 23A, SE-17165, Solna, Sweden. Electronic address: jesper.tegner@kaust.edu.sa.
² Bioscience Program, Bioengineering Program, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia; Mucosal and Salivary Biology Division, King's College London Dental Institute, London, UK; Translational Bioinformatics Unit, Navarrabiomed, Complejo Hospitalario de Navarra (CHN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Spain.

PMID: 35430125
DOI: 10.1016/j.tcb.2022.03.009

Abstract

Molecular profiling of clinical tissue samples is at the core of precision medicine. Yet, to elucidate the contribution of mixed cell types and detect changes in cell populations in response to infections or drugs is challenging. Recent advances using machine learning promise to learn explanatory models directly from data.

Keywords: bioinformatics; cell type; deconvolution; genomics; precision medicine.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Computational Biology*
Genomics*
Humans
Machine Learning
Precision Medicine