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Home  >  Speakers  >  Yinyin Yuan
Yinyin Yuan

Yinyin Yuan

London, England    United Kingdom
Pathology, Bioinformatics
Pathology, Computational Pathology,...More
Spoken at 2 events

Biography :

Yinyin joined the ICR in 2012 as the leader of the Computational Pathology and Integrative Genomics team. Trained as a computer scientist, she finished a 5-year BSc degree within 4 years (2003) at the University of Science and Technology of China, before obtaining her MSc (2005) and PhD (2009) at University of Warwick. At Warwick she became interested in studying genetic regulation in plant disease by leveraging statistical analysis tools originally developed for other disciplines such as economics.

Intrigued by the immense biological complexity underlying diseases, she started her postdoctoral research at the Cambridge Research Institute Cancer Research UK to characterise the molecular landscape of breast cancer. Together with an international research team, she discovered 10 new molecular subtypes of breast cancer in 2,000 patients. As a Junior Research Fellow at Wolfson College, University of Cambridge, she interacted with researchers from various backgrounds such as physics, engineering and humanity substantially benefitting her future research.

During her time in Cambridge, she realised how quantitative analysis can be developed into an elegant yet powerful approach to provide objective solutions in pathology, and how computer science can help achieve this. By training a computer to automatically identify cancer cells in pathological specimens just like how cameras recognise faces, a brand new modern framework can be built upon pathological observations with a wealth of knowledge accumulated over centuries. In doing so, the characteristics of diseases in hundreds of patients and their treatment strategies can be objectively evaluated to gain understanding about causal mutations and accordingly the best treatment.

At the ICR, her aim is to continue bringing in techniques from a broader range of fields to formulate unique approaches for linking genetic mutations, pathological observations and patient treatment.

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Pathology, Bioinformatics

Interested Topics

Pathology, Computational Pathology, Integrative Genomics, Genetic regulation, Plant disease, Statistical analysis tools, Molecular landscape, Breast cancer, Mutations, Patient treatment

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