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Dr Dimitris Parthimos

Senior Lecturer

School of Medicine

Overview

I am a bio-mathematician based at the Division of Cancer and Genetics. Over the past two decades I have been working closely with lab biologists and clinical academics, developing novel tools and approaches to understand cellular mechanisms of physiology and disease. I have been heading the mathematical/computational component in several collaborative projects, while leading a number of multi-disciplinary initiatives.

Publication

2021

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1996

Articles

Research

My recent work at the Division of Cancer and Genetics (DCG) employs bio-mathematical techniques we previously developed, towards the study of complex tissue microenvironment signalling in tumours. This involves studying the cellular origins of cancer, and disease manifestation at the organ and system levels. Research, closely aligned with the Tissue Microenvironment Group (TMEG), includes models of tumour vascularization as a conduit for tissue oxygenation and metabolic homeostasis. To facilitate this and related work on cancer cell division dynamics, we established international collaborations between US and UK partners.

I am also closely involved in prostate cancer research employing novel molecular biomarkers (associated with extracellular vesicle-mediated signalling) for the accurate characterisation of disease progression. Work involves machine learning classification technology that significantly improves prostate cancer diagnosis.

Work within DCG is underpinned by state-of-the-art bioimaging. I have been coordinating the image analysis sector of TMEG research, while leading initiatives towards standardization and provenance of experimental/analytical protocols. Work has led to an ongoing close cooperation with the US National Institute of Standards and Technology (NIST). We have installed pioneering NIST image analysis technology in Cardiffa and establish a consortium involving NIST, the University of Illinois and CompSci at Cardiff to develop artificial intelligence-assisted frameworks for bio-data analytics, towards future diagnostic modalities.

Within DCG, we work on mTOR pathways in cancer progression, and modelling telomere length changes in cancer cells.