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Knowledge Integration for Gene Target Selection

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Title: Knowledge Integration for Gene Target Selection


1
Knowledge Integration for Gene Target Selection
  • Graciela Gonzalez, PhD
  • Juan C. Uribe
  • Contact graciela.gonzalez_at_asu.edu

2
GeneRanker in a Nutshell
  • Integration of knowledge from
  • biomedical literature
  • curated PPI databases, and
  • protein network topology
  • Seeks to prioritize lists of genes on their
    association to specific diseases and phenotypes
    1,
  • Such associations may or may not have been
    published (thus, not text mining)

1 Gonzalez G, Uribe JC, Tari L, Brophy C, Baral
C. Mining Gene-Disease relationships from
Biomedical Literature Incorporating
Interactions, Connectivity, Confidence, and
Context Measures. Pacific Symposium in
Biocomputing 2007 Maui, Hawaii 2007.
3
GeneRanker Interface

  1. The user types a disease or biological process
    to be searched.
  2. Genes found to be in association to the disease
    are extracted from the literature.
  3. Protein-protein interactions involving those
    genes are then pulled from the literature
    curated sources
  4. The protein network is built and each gene ranked

4
GeneRanker Interface
Collaboration Application of GeneRanker to a
biological context, with Dr. Michael Berens,
Director of the Brain Tumor Unit at the
Translational Genomics Institute (TGen).
GeneRanker is available as an online
application at http//www.generanker.org.
  • Each gene is scored and can be annotated (count
    of co-occurrences and statistical representation)

5
Evaluation of GeneRanker
  • Contextual (PubMed search) based shows gt 20 jump
    in precision over NLP based extraction.
  • Synthetic network results show AUC gt 0.984
  • Empirical validation against a glioma dataset
    shows consistent results (118 vs 22
    differentially expressed probes from top vs
    bottom of list)

6
Complementary Work
  • CBioC www.cbioc.org shows PPIs, gene-disease,
    and gene-bioprocess associations extracted from
    abstracts
  • BANNER sourceforge.banner.org (presenting a
    poster on this one). An open source entity
    recognizer available now.
  • Gene normalization a similar open source system
    soon to be available.
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