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First Annual RECOMB Satellite Workshop on Massively Parallel
Sequencing
and
Third Annual RECOMB Satellite Workshop on Computational Cancer Biology
March 26-27 2011, Vancouver, BC, Canada
Massively Parallel Sequencing (RECOMB-seq)
The revolution in DNA sequencing opened many
possibilities for researchers working in the fields of genetic
variation, diseases of genomic origin, and even personalized
medicine. The new technologies can also be employed to discover
functional landscape of the human genome as part of the ENCODE
Project; such as epigenetic variation (methylation patterns
and histone modification) and protein-DNA interaction. Further
uses of the high-throughput sequencing technologies include
transcriptome analysis, non-coding RNA discovery, gene expression
profiling, rapid testing of genotype-phenotype associations,
and identification of pathogens.
Recent publication of the pilot phase of the
1000 Genomes Project demonstrated the feasibility and power
of massively parallel sequencing, yet also presented the challenges
in analyzing the data.
We would like to invite contributions presenting
new methods in algorithm development for the analysis of massively
parallel sequencing data. Problems of specific interest may
include, but are not limited to:
- Read mapping
- Discovery and genotyping of genomic
variants; including SNPs, indels, and structural variants
(deletions, novel insertions, inversions, duplications, translocations,
mobile element insertions)
- Local and de novo sequence
assembly
- Epigenetic variation such as methylation
profiling, ChIP-seq analysis, metagenomics
- Transcriptome analysis, RNAseq and
transcriptome assembly
Computational Cancer Biology (CCB)
Cancer biology is undergoing a revolution
driven by the application of high-throughput techniques such
as genome and transcriptome sequencing, high resolution genotyping arrays,
genome-wide epigenetic profiling, expression
microarrays, miRNA profiling, and mass spectrometry to tumor
samples. These techniques give rise to large collections of
data that are impacting both basic cancer biology as well as
clinical applications. Cancer is disease of tremendous complexity,
and thus the analysis and interpretation of this data, taking
a systems biology approach, demands sophisticated, specialized
computational methods.
Topics of interest include, but are not limited
to
- Methods for analysis of next generation sequencing data with a specific application to cancer
- Pathway analysis and network reconstruction with a focus on cancer biology
- Inference of genomic rearrangements, somatic mutations, gene expression, alternative splicing
from next gen sequencing data sets
- Copy number and allelic distribution analysis from high density SNP chips
- Epigenetic variation such as methylation profiling, methyl-seq, ChIP-seq analysis
- Transcriptome analysis, RNAseq and transcriptome assembly
- Data integration from multiple molecular assays
- Integration of clinical and molecular data
RECOMB-seq and CCB will be held in parallel, with shared sessions on
topics relevant to both workshops. We strongly encourage submission
of abstracts / manuscripts describing computational approaches
relevant to both RECOMB-seq and CCB.
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