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Day 1 & Day 2 - Next Generation DNA sequencing and bioinformatics
Day 3 - Genome-wide association studies
Day 4 - Biomolecular networks: analysis and inference
Day 5 - Computational neurobiology


Speakers' presentation:

  • Classic and next-gen technologies (David Miller)
  • Classic and next-gen assembly strategies (Annette McGrath)
  • De novo assembly approaches for second-generation sequence data (Mike Imelfort)
  • Issues of coverage with next-generation sequencing, and several applications (Daniel Marshall)
  • Development of bioinformatics approaches to extract information from metagenomic data produced by next-generation sequencing technologies (Lauren Bragg)
  • Next-generation assembly challenges (Sean Grimmond)

  • DAY 2
  • Transcriptomes 101 (including paired ends, mate pairs, and SNPs) (Nicole Cloonan)
  • Transcriptomics and other impossible things that can be done with orphan species (Lesley Collins)
  • Development of computational pipelines for microRNA profiling, chromatin modification (ChIP-Seq) and DNA methylation analysis (BI-Seq)(Roberto Barrero)
  • Metagenomics characterisation of microbial communities (Gene Tyson)
  • The future of next-gen (Sean Grimmond)

  • DAY 3
  • Genomic technologies and gene discovery in complex disease (Grant Montgomery)
  • Statistical analysis of genome-wide association study (GWAS) data (Jim Stankovich)
  • GWAS for quantitative traits (Peter Visscher)
  • Combinatorial optimisation models and algorithms for GWAS (Pablo Moscato)
  • Gene mapping with sequence data (Allan McRae)

  • DAY 4
  • Statistical inference of gene networks for computational drug-target pathway discovery (Seiya Imoto)
  • Visualisation and analysis of biological networks (Seokhee Hong)
  • Network reconstruction, topology and feasible solution space (Lars Nielsen)
  • Constraint-based reconstruction and analysis of metabolic and regulatory networks (Lars Nielsen)
  • An introduction to and demonstration of the Cytoscape application (Melissa Davis)

  • DAY 5
  • Brains and computers (Geoffrey Goodhill)
  • Contextual influences on perception [tutorial] (Tom Albright)
  • Associative learning and visual imagery (Tom Albright)
  • Computational models of the brain (Michael Breakspear)






    © ARC Centre in Bioinformatics 2009