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Cancer Bioinformatics Workshop, Cambridge 2010

Cancer Bioinformatics Workshop, Cambridge 2010

25 Videos · 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/.

Videos

Invited Speakers

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37:29

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

Keith A. Baggerly

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37:57

Gene expression state space models and cell fate transitions

John Quackenbush

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29:53

Towards Evidential Inference of Signalling Pathway Topologies

Mark Girolami

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31:48

Cancer-specific high throughput analysis of somatic mutations

Rachel Karchin

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34:24

Learning and retrieval from multiple sources

Samuel Kaski

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Draft
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24:33

Revealing cancer mutations using deep sequencing

Oliver Elemento

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25:50

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

Sayan Mukherjee

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Draft
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36:31

Identification of copy number alterations in tumor genomes using next-generation...

Peter J. Park

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Draft
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29:42

Oncogenic network identification from genomic data

Lodewyk Wessels

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33:17

Data-driven characterization of Receptor Tyrosine Kinase signalling networks in ...

Sach Mukherjee

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Lectures

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30:01

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

Julio Saez Rodriguez

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30:00

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

Andrew Menzies,

David Jones

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30:32

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

Mark van de Wiel

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Draft
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18:39

An integrated analysis of molecular aberrations in NCI-60 cell lines

Chen-Hsiang Yeang

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21:55

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

Marine Jeanmougin

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20:53

Non-Negative Matrix Factorisation finds Connections in Complex Data

Clare Lee

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15:04

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

Roland Schwarz

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28:51

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

Chris Greenman

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14:52

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

Stefano Berri

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15:54

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

Yinyin Yuan

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17:54

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

Kevin Bleakley

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17:42

Biomarkers Discovery in Breast Cancer by Interactome-Transcriptome Integration

Maxime Garcia

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Draft
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29:40

Joint SNP analysis using a breast cancer GWAS Data Set

Xia Jiang

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Draft
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31:28

Inferring transcriptional and microRNA-mediated regulatory programs in glioblast...

Christina Leslie

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22:59

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

Wessel van Wieringen

calendar icon Oct 11, 2010 2762 views

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