Biomedical Sciences Division (BioMed)

Decoding Life, Advancing Health

Overview

The Biomedical Sciences (BioMed) division at KAUST brings together world-class science, technology, and education to address today’s most pressing health challenges. Through interdisciplinary research, advanced computational and digital tools, and strong partnerships across the healthcare ecosystem, BioMed connects discovery with real-world impact - supporting national priorities while contributing to global advances in health and disease.

Vision

BioMed will improve health in Saudi Arabia and beyond by harnessing cutting edge science and technology to investigate, educate on, and translate discoveries that make people’s lives better.

Mission

BioMed applies the scientific and technical expertise of KAUST by interdisciplinary collaboration and intersectional partnerships both within and beyond the university, leveraging and boosting the efforts of the health care ecosystem to understand, prevent, and treat disease.

We will encourage, educate, and promote expertise in the study and taming of disease to help engineer a healthier life for all, using knowledge generation with widespread deployment of health-translated advances underpinned by our cutting edge, world class technical expertise.

A Message from the Dean of Biomedical Sciences (BioMed)

Professor Peter J Goadsby FMedSci FRS

BioMed is KAUST's newest division, harnessing the University's world-class science and technology to advance healthcare outcomes in Saudi Arabia and beyond. We apply cutting-edge computational and digital tools to understanding, combating and preventing disease.

BioMed is at the start of an exciting journey. The division offers a collaborative environment where scientific excellence meets a passion for teaching and mentoring a new generation of graduates who will advance health in the 21st century.

Our priorities are those of the Kingdom, our mission aligned with Vision 2030's aspirations for better health. Our graduate programs uniquely integrate biology with engineering and bioinformatics and, our faculty and students strive to be future-ready for the rapidly emerging challenges and opportunities in biomedical science.

BioMed draws on the KAUST ecosystem of outstanding research and technical capabilities, all set against the backdrop of the Red Sea. We are beginning an ambitious journey, and invite those who share our vision of a healthier life for all.

View the Dean’s Biography

Our Programs

Bioengineering

Bioscience

David Gomez-Cabrero

Associate Professor, Bioscience

Biomedical Sciences

Research Platform Membership: The Bioinformatics Platform

david.gomezcabrero@kaust.edu.sa

AI for Biomedicine Lab

Building frameworks that help transform (vast) multimodal biomedical data into knowledge that improves how we understand and treat disease.

Program Affiliations

Research Interests

Professor Gomez-Cabrero is a bioinformatician and computational biologist. His research focuses on the development of system-based methodologies for understanding biological systems and its translational applications for understanding health and disease. Upon completing his Ph.D., he moved to Stockholm as postdoctoral research. Next, he was appointed Assistant Professor at Karolinska Institutet between 2014 and 2018. Next, he was appointed as Senior Lecturer at King's College London (2016-2018). During 2017 he became the head of the Translational Bioinformatics Unit at Navarrabiomed (Pamplona, Spain). His current goals are the developing of robust statistically-based methodologies and frameworks to uncover robust hypothesis in (possibly under-powered) research studies. Tools for multi-omic integration are being implemented and shared in the Bioconductor STATegRa package. Nowadays, the aim is to develop strategies for current integrative challenges such as "integrating bulk and single-cell data" and "integrating multi-omic single-cell data". Most of Professor Gomez-Cabrero's research is conducted in a translational context, especially working in Multiple Sclerosis, Rheumatoid Arthritis, rare diseases and Myelodysplastic syndromes, among others.

Computational Biology Multi-omics data integration Single-cell Spatial Profiling Bone Marrow

Education Profile

Postdoctoral Fellow, Karolinska Institutet, 2009-2014.
Ph.D. Mathematics, Universitat de València, 2005-2009.
Advances Ph.D. Courses in Operations Research and Statistics, Universitat de València, 2000-2003.
MSc Statistics, 2000-2004.MSc and BSc Mathematics, 1996-2000.

Publications

Google Scholar: https://scholar.google.com/citations?user=lbKdoNsAAAAJ&hl=en&oi=ao

McManus et al. (2025). NLRP3-mediated glutaminolysis and Alzheimer’s progression. Immunity. https://doi.org/10.1016/j.immuni.2025.01.007

Ortega-Legarreta et al. (2024). ClustAll: R package for patient stratification. PLOS Comput Biol. https://doi.org/10.1371/journal.pcbi.1012656

Buenaventura et al. (2024). Competition and X-linked genetic diversity. Nat Genet. https://doi.org/10.1038/s41588-024-01840-5

Massoni-Badosa et al. (2024). Human tonsil cell atlas. Immunity. https://doi.org/10.1101/2022.06.24.497299

Palomino-Echeverria et al. (2024). Stratification in decompensated cirrhosis. J Transl Med. https://doi.org/10.1186/s12967-024-05386-2

Larrayoz et al. (2023). Predicting immunotherapy outcomes in myeloma. Nat Med. https://doi.org/10.1038/s41591-022-02178-3

Lasaga et al. (2023). Gene therapy in Fanconi anemia. Haematologica. https://doi.org/10.3324/haematol.2022.282418

Ye et al. (2022). Hematopoietic stem cell microenvironment. iScience. https://doi.org/10.1016/j.isci.2022.104225

Ewing et al. (2020). GeneSetCluster for gene-set analysis. BMC Bioinformatics. https://doi.org/10.1186/s12859-020-03784-z

Research Areas

Computational Bioscience
Machine Learning

Multimedia

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