Computational Biology

MEDICAL BIOTECHNOLOGY

Research Interests

Artificial intelligence and machine learning for multi-omics analysis and therapeutic discovery. RNA regulation, RNA-binding proteins and extracellular vesicles in cancer and neurodegeneration. Cancer metabolism, tumour immunity and drug resistance. Comparative microbial genomics, antimicrobial resistance and plant-associated microbiomes.

Description of Research

The Computational Biology Group studies how changes in gene regulation and molecular interactions contribute to disease. We combine genomic, transcriptomic, proteomic, metabolomic and clinical data to identify disease mechanisms, candidate biomarkers and therapeutic targets. Artificial intelligence and machine learning are central to our research direction, supporting the integration of these datasets and the prioritisation of hypotheses for experimental testing.

Our work on RNA biology examines how RNA-binding proteins, microRNAs and alternative splicing regulate cell behaviour. We investigate APE1 and HuR, with particular interest in RNA processing, extracellular vesicle cargo and communication between cells. These studies connect RNA regulation to cancer progression, inflammation and neurodegeneration, including altered communication between neurons and glial cells in amyotrophic lateral sclerosis.

In cancer, we analyse how oncogenic alterations reshape metabolism, gene expression and the tumour microenvironment. Recent collaborative studies have examined p53-associated metabolic changes in breast cancer brain metastasis and the role of miR-30d in suppressing innate immune responses. Integrating molecular profiles with functional experiments helps us identify dependencies that may be explored as therapeutic targets.

We are extending our computational drug discovery work by combining AI methods with structural modelling, molecular docking and molecular dynamics simulations. Current interests include small molecules targeting RNA-binding proteins such as HuR and APE1. The aim is to prioritise compounds for experimental evaluation and understand how they may affect protein function and RNA interactions.

Our research also addresses microbial adaptation, antimicrobial resistance and plant-associated microbiomes. Comparative genomics and metagenomics help us connect genetic variation and protein function to microbial phenotypes, and investigate bacterial communities relevant to plant health and sustainable agriculture.

We work closely with experimental groups and train researchers in bioinformatics, omics analysis, and the use of AI in biological research. Through joint projects and training, we support research capacity in ICGEB Member States, with particular attention to low- and middle-income countries.

The Group maintains an extensive international network, with collaborations that include ICGEB Collaborative Research Programme projects with research groups in Romania, Kazakhstan, Pakistan and Serbia.

Recent Publications