Incorporating Pathways

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Incorporating Pathways
3rd DNA Microarray Workshop 31 Dec. 2003
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The Challenge

• How do we relate our understanding of biological
  pathways to the new high-throughput genome
  technologies?
• One way would be to superimpose data derived from
  these technologies on pathway maps

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Traditional solutions

• GenMAPP
• DAVID
• Powerpoint

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(from the GenMAPP website)
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Problems with traditional solutions

• Small number of pathways
• Pathways are not linked to one another
• Defining new pathways is complicated and
  time-consuming
• Representation is static and does not allow
  interactive manipulation by viewer

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SHARP
SHowcase of ATM-Related Pathways

• Database of pathways
• Constantly updated by the community
• Curated and supervised by a steering committee
• Visualization tool
• Constructs graphical pathway maps based on
  database
• Allows searching for new functional links
• Superimposes gene expression data on map
• Algorithmic Engine
• Traverses the network in order to gain new links

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SHARP Expression

• Both absolute (Affymetrix) and relative (cDNA)
  data is supported
• Genes are identified by their LocusLink IDs
• Multiple pathways, datasets and conditions can be
  viewed and compared in a single session
• Expression view is highly configurable (data
  parameters, coloring scheme)

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SHARP - Clustering

• The SHARP viewer also enables incorporation of
  clustering data
• Any partition of the genes into groups (generated
  by clustering algorithms, GO annotations, etc.)
  can be used
• Genes are identified by their LocusLink IDs
• Both clustering and bi-clustering are supported

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CASP3 (Apoptosis)
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SHARP
Nir Orlev Rani Elkon Yossi Shiloh Ron Shamir