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Programme and Abstracts

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Programme at a glance

Posters

 

The data generated by medical care and medically relevant research are rapidly becoming bigger and more complex, particularly with the advent of new technologies. Our ability to advance medical care and efficiently translate science into modern medicine is bounded by our capacity to access and process these big data. From human genetics and pathogen genomics to routine clinical documentation, from internal imaging to motion capture, from digital epidemiology to pharmacokinetics, and from treatment pathways to life course assessment, the big Vs of Big Data - volume, variety, velocity and veracity - abound in medicine. Statistical, mathematical, visualisation, and computational approaches, from a wide range of disciplines, as well systems for innovative ICT-based interventions are needed to keep apace of the complexity in Big Data and to advance medicine.

On 19th June 2015 at the Cancer Research UK Cambridge Institute, Cambridge-based researchers from all Schools of the University and local research institutes, the pharmaceutical industry and our funding and commissioning partners met for an afternoon of talks demonstrating methods and opportunities for harnessing Big Data in medicine.  

Read the abstracts and selected presentation slides below. 

 

Programme at a glance 

 

12:00

Registration , Lunch & Poster Session

 

13:00

Opening remarks

Patrick Maxwell , Regius Professor of Physic

 13:10-14:50

Session 1: Exemplars

Chairs: Simon Tavaré (CRUK-CI/DAMTP), John Aston (DPMMS)

13:10

Keynote: Statistical challenges in the analysis of genomic data

Sylvia Richardson, Director, MRC Biostatistics Unit

 

Building Insight Into Disease and Therapy from Real-World Evidence Using Graphs and Large-Scale Analytics

Nirmal Keshava, AstraZeneca R&D Information

 

Undiscovered Scientific Knowledge from Large Unstructured Text Collections in an Era of Big Data

Nigel Collier, Department of Theoretical and Applied Linguistics

 

Integrating Chemical and Biological Data for Drug Discovery

View Slides 

Andreas Bender, Centre for Molecular Informatics, Department of Chemistry

 

Mapping the information processing pathways of the cortex: challenges and opportunities

View Slides

Andrew Thwaites, Psychology Dept, Cambridge University & MRC-CBSU

14:50-15:10

Break

 

15:10-16:50 

Session 2: Opportunities

Chairs: Lydia Drumright (Department of Medicine), John Todd (Cambridge Institute for Medical Research)

 

Keynote: Clinical Informatics

Afzal Chaudhry, BRC, Chief Clinical Information Officer

 

EMBL-EBI Big Data in Medicine Strategy

Paul Flicek, European Bioinformatics Institute

 

Smartphones, Big Data, and Psychiatry

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Neal Lathia, Computer Laboratory, and Conor Farrington, Cambridge Centre for Health Services Research, Institute of Public Health

 

Treatment Pathways in Cancer Data

Brian Shand, National Cancer Registration Service, Public Health England

 

High-Content Microscopy and Big Data: Discovering the genes and pathways that control cells in health & disease

Rafael Carazo Salas, Department of Genetics

 16:50-17:10

Poster talks

 

 

Mathematical Methods for Automatic Detection and Tracking of Dividing Cancer Cells in Phase Contrast Microscopy

Joana Sarah Grah, Department of Applied Mathematics and Theoretical Physics

 

Statistical tools for single cell gene expression analysis

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Daphne Ezer, Department of Genetics/Cambridge Systems Biology Centre

 

From big data to big model: a probabilistic approach to infer cancer evolution

Ke Yuan, Cancer Research UK Cambridge Institute

17:10

Closing remarks

Keith McNeil, CUH Foundation Trust CEO

17:30-19:00

Drinks & Poster Session

 

 

Posters

Sketch-driven Data Analysis

Neil Satra, University of Cambridge Computer Laboratory

Limitations of de-identification: no reason not to share data

Download Poster

Neil Walker, Department of Medical Genetics

Non-negative matrix tri-factorisation with missing values, applied to drug sensitivity prediction

Thomas Alexander Brouwer, Computer Lab, University of Cambridge

Mineotaur: interactive visual analytics for high-content microscopy screens

Balint Antal, Department of Genetics, University of Cambridge

Molecular principles by which gene fusions affect protein interaction networks in cancer

Natasha Latysheva, MRC Laboratory of Molecular Biology

High-dimensional statistical approaches for heterogeneous molecular data in cancer medicine

Frank Dondelinger, MRC Biostatistics Unit

A computational approach to the genetic basis of antigenic change in influenza A

Sarah James, Department of Zoology

Performing large scale conditional analysis in GWAS: How to better exploit summary statistics?

Paul Newcombe, MRC Biostatistics Unit

Empirical Bayes in Genomics: when dimensionality is a blessing

Gwenael G.R. Leday, MRC Biostatistics Unit, Cambridge

Analysis of Iterative Screening with Stepwise Compound Selection Based on Novartis in-house HTS Data

Shardul Paricharak, Department of Chemistry

Little Data, Big Health

Wei Wang, Little Data Labs

Baal-ChIP: Allele-specific ChIP-seq analysis from cancer cell lines

Ines de Santiago, CRUK - Cambridge Institute

The potential of hyperspectral imaging in fluorescent contrast enhanced imaging

Anna Siri Luthman, Department of Physics and Cancer Research UK Cambridge Institute

The ContentMine

Jenny Molloy, Cambridge Synthetic Biology SRI, The ContentMine