Contact information
Websites
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Cribbslab website
The cribbslab laboratory website
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Personal website
My personal website detailing my background, code and personal opinions
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Linkedin
Linked in website
Colleges
Adam Cribbs
ASSOCIATE PROFESSOR
- MRC Career Development Fellow
Prof Cribbs leads a computational biology team with a broad interest in systems biology, immunology, epigenetics, and machine learning-driven approaches to biomedical research.
He completed his PhD in molecular T cell immunology at Imperial College London in May 2013. He then undertook a two-year postdoctoral position investigating the epigenetics of T cell activation at the University of Oxford. Following this, he completed a three-year MRC Fellowship in Computational Biology (Computational Genomics and Training Centre (CGAT) programme) with Prof Chris Ponting, also at the University of Oxford. Upon completion of this fellowship, he was appointed Group Leader in Systems Biology in 2018 and MRC Career Development Fellow (2021–2026) at the Botnar Research Centre.
Research in the Cribbs lab integrates functional genomics with advanced machine learning approaches to understand disease biology. A key focus is the development and application of graph-based neural networks, causal machine learning, and Agentic AI systems to identify regulatory mechanisms governing gene expression, protein interactions, and biological pathways. By leveraging these methodologies, the lab aims to decipher disease processes and uncover novel therapeutic targets.
Key publications
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Correcting PCR amplification errors in unique molecular identifiers to generate absolute numbers of sequencing molecules
Preprint
Sun J. et al, (2023)
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A roadmap for delivering a human musculoskeletal cell atlas.
Journal article
Baldwin M. et al, (2023), Nat rev rheumatol, 19, 738 - 752
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Nanopore sequencing of single-cell transcriptomes with scCOLOR-seq.
Journal article
Philpott M. et al, (2021), Nat biotechnol, 39, 1517 - 1520
Recent publications
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Cellular and molecular landscapes of human tendons across the lifespan revealed by spatial and single-cell transcriptomics
Preprint
Kurjan A. et al, (2025)
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Chromatin-focused genetic and chemical screens identify BRPF1 as a targetable vulnerability in Taxol-resistant triple-negative breast cancer.
Journal article
Yedier-Bayram O. et al, (2025), Exp mol med, 57, 1294 - 1307
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Functional Genomic Screens Reveal RBBP4 as a Key Regulator of Cell Cycle Progression in TMZ-Resistant Glioblastoma
Preprint
Kala EY. et al, (2025)
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Exploring cellular changes in ruptured human quadriceps tendons at single-cell resolution.
Journal article
Mimpen JY. et al, (2025), J physiol
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PyPropel: a Python-based tool for efficiently processing and characterising protein data.
Journal article
Sun J. et al, (2025), Bmc bioinformatics, 26