Events calendar

WORKSHOP | Mathematical Oncology

21 Feb 2023, 13:00 PM

Methodologies for Multi-Modal Analysis of Biological and Clinical Datasets



We are delighted to announce that the CRUK Convergence Science Centre will hold an in-person workshop addressing the importance of Mathematical Oncology in the analysis of multi-modal biological and clinical datasets. This workshop will be taking place at the Centre's space on Tuesday 21st February 2023 from 13.00-16.00.

 

Cancer research has now become indissociable from multi-modal datasets. Combining spatial and temporal multi-OMICs with digital pathology, pathway analyses and medical imaging, it has never been more challenging to make use of the wealth of biological and clinical data that can be collected. But what purpose serves the culmination of Big Data if they cannot be meaningfully resolved?

 

Mathematical Oncology was born at the interface between cancer research and mathematics. It uses the power of applied mathematics, computation, and machine learning to model, stimulate and illuminate our understanding of complex biological processes by deciphering the hidden codes behind the intersections of multi-modal data.

 

The CRUK Convergence Science Centre is committed to using Data Science to enable discoveries in the fight against cancer. To this aim, we wish to unite cancer researchers and mathematicians from across the Institute of Cancer Research and Imperial College London in the same room. 

 

 

 

Are you a cancer researcher or clinician in the possession of substantial multi-modal datasets?

Are you a biomathematician, statistician, bioinformatician, or machine learning specialist with experience in innovative solutions for multi-modal dataset analyses? 

Register to our workshop here!

 

 

Please note: This workshop is exclusively available to colleagues from the Institute of Cancer Research, the Royal Marsden, Imperial and Imperial College Healthcare. Due to space limitation, only one postdoctoral fellow or one PhD student will be admitted per lab.