̽��ֱ�� of Cambridge - Simon Tavare

̽��ֱ��Royal Society announces 2018 Fellows

cjb250 — Wed, 09 May 2018 14:26:31 +0000

̽��ֱ��50 newly-elected Fellows announced today join a list of scientists, engineers and technologists from the UK and Commonwealth. Past Fellows and Foreign Members have included Newton, Darwin and Einstein.

̽��ֱ��Cambridge academics announced today as Royal Society Fellows are:

Alexander Dawid, Emeritus Professor of Statistics, Department of Pure Mathematics and Mathematical Statistics
Gregory Hannon, Royal Society Wolfson Research Professor of Molecular Cancer Biology and Director, Cancer Research UK Cambridge Institute
Judy Hirst, Deputy Director, MRC Mitochondrial Biology Unit
Lalita Ramakrishnan, Professor of Immunology and Infectious Diseases and Head of Molecular Immunity Unit, Department of Medicine

Sir Venki Ramakrishnan, President of the Royal Society, says: “Our Fellows are key to the Royal Society’s fundamental purpose of using science for the benefit of humanity. For their outstanding contributions to research and innovation, both now and in the future, it gives me great pleasure to welcome the world’s best scientists into the ranks of the Royal Society.”

̽��ֱ��new Fellows will be formally admitted to the Society at the Admissions Day ceremony in July, when they will sign the Charter Book and the Obligation of the Fellows of the Royal Society.

View the full list of new Fellows and Foreign Members

Four Cambridge academics are among the new Fellows announced today by the Royal Society and chosen for their outstanding contributions to science.

For their outstanding contributions to research and innovation, both now and in the future, it gives me great pleasure to welcome the world’s best scientists into the ranks of the Royal Society

Sir Venki Ramakrishnan

Royal Society

Professor Simon Tavare elected as a Foreign Member of US National Academy of Sciences

Professor Simon Tavare, former Director of the Cancer Research UK Cambridge Institute, has been elected as a Foreign Member of the US National Academy of Sciences.

Professor Tavare works at the interface of the mathematical sciences and the biological and medical sciences. He pioneered probabilistic and statistical aspects of coalescent theory, full likelihood-based methods for sequence variation data, methods for ancestral inference, evolutionary approaches to cancer, and approximate Bayesian computation for inference in complex stochastic processes.

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. For image use please see separate credits above.

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World-leading cancer expert to head-up Cambridge Institute

gm349 — Fri, 21 Dec 2012 09:00:15 +0000

Simon Tavaré, a Fellow of the Royal Society and the Academy of Medical Sciences, has been a Professor of Cancer Research in the Oncology Department and Professor of Applied Mathematics and Theoretical Physics at the ̽��ֱ�� of Cambridge since 2003. He will take up his new post in February 2013, succeeding Professor Sir Bruce Ponder.

Professor Tavaré is a world-leading expert on probability, statistics and the biological and medical sciences. Much of his work has focused on the development of statistical methods that can help our understanding of cancer including aspects of population genetics, cancer genomics and DNA sequencing.

Professor Tavaré said: “I’m thrilled to be taking on this exciting new role. We will make further strides in our understanding of cancer while enhancing the international reputation of the Cancer Research UK Cambridge Institute. Our understanding of cancer is at a turning point. We are uncovering more of cancer’s secrets – and these secrets are taking us down new avenues of research that can lead to better treatments. Cancer research is indeed in an unprecedented age of discovery.”

̽��ֱ��Cambridge Institute is one of Cancer Research UK’s five institutes, playing a key role in its world-class research to find new ways to tackle cancer. Each year, thanks to the generosity of its supporters, Cancer Research UK invests £21m in the Institute to support this work.

Patrick Maxwell, Regius Professor of Physic and Head of the School of Clinical Medicine at the ̽��ֱ�� of Cambridge, said: "I am delighted that Professor Tavaré will be leading the Cambridge Institute. One of my main aims in Cambridge is to cross-fertilise different disciplines and Simon's work applying mathematical approaches to understanding cancer is a fantastic example of how powerful this can be."

Dr Harpal Kumar, Cancer Research UK’s chief executive, said: “It’s a great pleasure to announce Professor Tavaré as the new director of the Cancer Research UK Cambridge Institute. His research into statistical modeling and its application to genomics and cancer has earned him worldwide recognition. These are some of the new frontiers of cancer research that will yield more discoveries. ̽��ֱ��significant challenges that cancer poses are not insurmountable, and we look forward to Simon leading our Cambridge Institute in carrying out the high-impact research that will help us to cure more cancers sooner.”

̽��ֱ��Cancer Research UK Cambridge Institute is a major research centre which aims to take the scientific strengths of Cambridge to practical application for the benefit of cancer patients. ̽��ֱ��Institute is a unique partnership between the ̽��ֱ�� of Cambridge and Cancer Research UK. It is housed in the Li Ka Shing Centre, a state-of-the-art research facility located on the Cambridge Biomedical Campus which was generously funded by Hutchison Whampoa Ltd, Cambridge ̽��ֱ��, Cancer Research UK, ̽��ֱ��Atlantic Philanthropies and a range of other donors. For more information visit www.cruk.cam.ac.uk.

Copy courtesy of CRUK.

̽��ֱ�� ̽��ֱ�� of Cambridge and Cancer Research UK have appointed Professor Simon Tavaré to be the next director of the Cancer Research UK Cambridge Institute.

I am delighted that Professor Tavaré will be leading the Cambridge Institute. One of my main aims in Cambridge is to cross-fertilise different disciplines and Simon's work applying mathematical approaches to understanding cancer is a fantastic example of how powerful this can be.

Patrick Maxwell, Regius Professor of Physic and Head of the School of Clinical Medicine at the ̽��ֱ�� of Cambridge

Credit Dr David Becker, Wellcome Images

Breast cancer cells

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Data mining the complex cancer landscape

bjb42 — Mon, 04 Jan 2010 14:27:17 +0000

̽��ֱ��advent of new technologies has enabled researchers to interrogate human genomes at unprecedented resolution. These technologies have led to a wealth of genomic information that has the capacity to shed new light on complex diseases, but they also generate far too much data to interpret by eye. Consequently, novel computational and statistical techniques have evolved to extract meaningful patterns from the data (‘data mining’) and to integrate this with other types of biological information in an attempt to make sense of what it all means.

In Cambridge, a collaboration between the Computational Biology group at the Cancer Research UK Cambridge Research Institute (CRI), led by Professor Simon Tavaré (also at the Department of Applied Mathematics and Theoretical Physics), and Professor Carlos Caldas and Dr James Brenton (who are both at the CRI and the Department of Oncology) seeks to do just this, demonstrating the power of combining expertise in statistics, computational and experimental biology, and clinical medicine to understand cancer.

METABRIC

Breast cancer, like other malignancies, is driven by the progressive acquisition of key genetic alterations that confer growth advantages on the cell. Most of the acquired aberrations are merely ‘passenger’ events that do not influence cancer progression, whereas the ‘driver’ events are critical mediators of disease. It is these ‘driver’ events and the effects they elicit that researchers seek to identify, the problem being akin to searching for a needle in a haystack.

METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) is an Anglo-Canadian effort aimed at finding the ‘needles’, and is funded by Cancer Research UK and the British Columbia Cancer Foundation. Given the substantial molecular heterogeneity among breast cancer patients, METABRIC seeks to interrogate the genomic and transcriptional landscape of over 2,000 clinically annotated breast tumour specimens to generate a robust molecular description of the disease.

Each sample is examined for differences in gene expression levels, as well as for alterations in the number of copies of each gene, by combining measurements from nearly two million probes that query the genome at sequential positions. Add to this a variety of other data types and five years of clinical history, and you wonder how the sheer volume of data can be processed,

let alone interpreted. In fact, a major challenge with such high-dimensional datasets is the identification of true differences amid inherent background noise. How can one see the forest for the trees in the cancer genome landscape?

Seeing the forest for the trees

Dr Christina Curtis in the Computational Biology group is leading the analysis of massively parallel technologies using computational and statistical methods to make sense of this vast data deluge. Much of her research relies on high-performance computing to process these and other large datasets. Fortunately, the CRI houses a computer cluster with nearly 500 cores and multiple high-memory nodes that will expand to meet the growing need for computational capacity.

Using novel analytical approaches for data integration and mining, Dr Curtis and her team have defined additional subtypes of breast cancer based on their unique molecular characteristics, providing fresh insight into mechanisms of breast cancer tumourigenesis. Future work will relate these molecular profiles to specific clinical phenotypes and identify markers that improve the classification of breast cancer. Importantly, the techniques employed for METABRIC are sufficiently general to be applied to a variety of other cancer datasets.

Computational biology is providing the means to navigate through large-scale, multi-dimensional datasets. In doing so, it can help to build a holistic, systems-level perspective on cancer that will shape future clinical practice.

For more information, please contact Professor Simon Tavaré (st321@cam.ac.uk) and Dr Christina Curtis (cc529@cam.ac.uk) at the Cancer Research UK Cambridge Research Institute/Li Ka Shing Centre.

Computational biology is helping scientists to navigate through the data deluge generated from the analysis of cancer genomes.

Christina Curtis

Data mining

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