Cancer Bioinformatics Workshop, Cambridge 2010

Cancer Bioinformatics Workshop, Cambridge 2010

18 Lectures · Sep 2, 2010

About

Substantial amounts of data are being generated within cancer research. Datasets range from gene expression and microRNA array data through to next generation sequence data. Data interpretation draws on mathematical and computational skills and thus the subject has engaged the interest of researchers in areas such as machine learning, statistics, bioinformatics and computer science. The goal of this cross-disciplinary Workshop is therefore to bring together researchers from these disciplines and cancer researchers who have an interest in data analysis, to explore and present innovative approaches to this subject. Presented papers should:

  1. Propose novel data analysis methods applicable to this domain or:
  2. Present bioinformatics-driven studies in which mathematical or computational methods played an important role in finding results of potential significance in cancer research.

For novel data analysis methods, a non-exhaustive list of suitable topics include:

* Unsupervised, semi-supervised and biclustering methods to highlight disease subtypes or dysregulated genes within these subtypes,
* Data integration/data fusion methods to integrate different types of data such as gene expression, microRNA expression and array CGH data,
* Inference of gene regulatory networks,
* Pathway modeling and probabilistic ranking of pathway models,
* Biomarker discovery,
* Genome-wide association studies,
* Rational drug design methods and chemoinformatics,
* Protein function, structure prediction and structural bioinformatics,
* microRNA target site prediction,
* Analysis of high throughput sequencing data,
* Gene expression and post-transcriptional regulation,
* Methods for the detection of fusion genes,
* Prediction of disease progression,
* Probabilistic inference, Bayesian methods and Kernel-based methods for classifier design with applications to cancer bioinformatics,
* Methods for the detection and quantification of copy number alterations and deletions.

The Workshop is principally focused on the intepretation of omics datasets and does not cover related areas such as cancer imaging or development of software tools unless in the context of novel methodology.

More about the workshop at http://www.enm.bris.ac.uk/cig/cb/.

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Uploaded videos:

Invited Speakers

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29:53

Towards Evidential Inference of Signalling Pathway Topologies

Mark Girolami

Oct 11, 2010

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4087 Views

Invited Talk
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37:57

Gene expression state space models and cell fate transitions

John Quackenbush

Oct 11, 2010

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4549 Views

Invited Talk
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31:48

Cancer-specific high throughput analysis of somatic mutations

Rachel Karchin

Oct 11, 2010

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4495 Views

Invited Talk
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25:50

Integrating genetic and gene expression evidence into genome-wide association an...

Sayan Mukherjee

Oct 11, 2010

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3904 Views

Invited Talk
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34:24

Learning and retrieval from multiple sources

Samuel Kaski

Oct 11, 2010

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3441 Views

Invited Talk
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37:29

The Importance of Reproducible Research in High-Throughput Biology: Case Studies...

Keith A. Baggerly

Oct 11, 2010

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41758 Views

Invited Talk

Lectures

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30:01

Uncovering signalling differences between primary and transformed hepatocytes us...

Julio Saez Rodriguez

Nov 29, 2010

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3363 Views

Lecture
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28:51

Estimating Rearrangement Evolution in Cancer with Massively Parallel Paired End ...

Chris Greenman

Oct 11, 2010

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3241 Views

Lecture
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15:54

Differential regulation of gene expression by copy-number alterations in cancer ...

Yinyin Yuan

Oct 11, 2010

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4366 Views

Lecture
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17:54

Fast joint segmentation of multiple array CGH profiles for detecting frequent co...

Kevin Bleakley

Oct 11, 2010

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3171 Views

Lecture
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14:52

An algorithm to detect copy number aberrations in cancer genomes of tumour speci...

Stefano Berri

Oct 11, 2010

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3064 Views

Lecture
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22:59

A random coefficients model for regional co-expression associated with DNA copy ...

Wessel van Wieringen

Oct 11, 2010

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2741 Views

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30:32

Spatial clustering of array CGH features in combination with hierarchical multip...

Mark van de Wiel

Oct 11, 2010

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3004 Views

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15:04

Finite-state transducers for inferring tumour evolution from copy number variati...

Roland Schwarz

Oct 11, 2010

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3004 Views

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30:00

Developing a substitution calling algorithm to analyse breast cancer exomes by n...

Andrew Menzies,

David Jones

Oct 11, 2010

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4688 Views

Lecture
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21:55

A comprehensive analysis combining network inference and pathway analysis for tr...

Marine Jeanmougin

Oct 11, 2010

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3568 Views

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17:42

Biomarkers Discovery in Breast Cancer by Interactome-Transcriptome Integration

Maxime Garcia

Oct 11, 2010

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4541 Views

Lecture
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20:53

Non-Negative Matrix Factorisation finds Connections in Complex Data

Clare Lee

Oct 11, 2010

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3985 Views

Lecture