Biomedical Intelligence Lab
Integrating Biology, Immunology, and Artificial Intelligence for Precision Medicine. An independent research initiative producing clinically meaningful discoveries in oncology and immunology.
Our mission
We bridge experimental biology with computational intelligence to produce discoveries that reach the clinic — from biomarker to bedside.
- Publications
- 40+
- Active projects
- 6
- Research themes
- 5
- Collaborators
- 12
Research themes
Five interconnected pillars
Each theme spans a set of tightly-linked sub-topics and projects, from wet-lab biology to computational modelling.
Computational Oncology
- Cancer biomarkers
- Survival prediction
- Precision oncology
- Multiomics
AI for Biomedicine
- Machine learning
- Deep learning
- Explainable AI
- Prediction models
Cancer Immunology
- Macrophage biology
- Tumour microenvironment
- Checkpoints
- Immunotherapy
Bioinformatics
- RNA-seq
- Single-cell
- Pathway analysis
- Network biology
Drug Discovery
- Docking
- MD simulation
- Virtual screening
- Repurposing
Featured projects
Work happening in the lab now
AI Models for Cancer Diagnosis
Deep-learning models that classify tumour subtypes from histopathology and multi-omics profiles.
View projectMachine Learning in Immunotherapy
Predicting patient response to immune-checkpoint therapy from tumour and immune-repertoire data.
View projectMacrophage Polarization
Single-cell resolution of macrophage states in the tumour microenvironment and their therapeutic switches.
View projectLatest publications
Peer-reviewed science, freshly out
- Journal
A multi-omics deep learning framework identifies prognostic subtypes in metastatic melanoma
Adelusi TI, Okafor J, Nakamura Y, et al.
Nature Communications · 2025
DOI: 10.1038/s41467-025-00000-0
PDFCite · DOI - Review
Explainable AI in precision oncology: from black-box models to clinically actionable insight
Adelusi TI, Chen L, Al-Fahim M
Cell Reports Medicine · 2025
DOI: 10.1016/j.xcrm.2025.101234
PDFCite · DOI - Preprint
Single-cell landscape of macrophage polarization in colorectal cancer response to anti-PD-1
Okafor J, Adelusi TI, García-Ramos P, et al.
bioRxiv · 2025
DOI: 10.1101/2025.03.14.598234
PDFCite · DOI
Principal Investigator
Dr. Temitope Isaac Adelusi
Computational biologist working at the intersection of machine learning, cancer immunology, and precision medicine. His lab develops interpretable models that translate high-dimensional biological data into clinical insight.
Learn with us
Free educational resources
Notebooks, tutorials, and guides for students and clinicians starting in computational biology.
Join us
Work at the frontier of biology and intelligence.
We're recruiting PhD students, postdocs, and MSc trainees, and partnering with hospitals and biotech on translational projects.