Text Mining

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Mark Maslyn at Ignite night at the Denver Open Source Users Group

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Text Mining

  1. 1. Chains of Amino Acids that fold into unique shapes that determine which other proteins can interact with them. Diagram From WikiMedia Commons
  2. 2. Diagram From WikiMedia Commons
  3. 3. Substrate Enzyme (Protein) (Protein) 1). + 2). + + e.g. PO 4- Product Enzyme
  4. 4. Start 1st Level 2nd Level From Bolouri (2008) – Used By Permission
  5. 5. Too Much Prot > Prot > Prot Glucose Glycogen ( Sugar ) ( Fat ) Prot < Prot < Prot Too Little
  6. 6. These Networks Can Lead to New Treatments Image From WikiMedia Commons
  7. 7. 2,000 New Citations Every Day !
  8. 8. From Bali(2009)
  9. 9. S p1 a p2 Where : p1 and p2 = different protein names (e.g. p53, BRCA1, etc) a = action verb (e.g. regulate, interact, modulate, bind, etc)
  10. 10. Retrieve Parse Filter and Rules Output in Transform Processing Cytoscape Format
  11. 11. One Level Tree Statistics: 200 References 7 Unique Links
  12. 12. Two Level Tree Statistics: 1600 References 25 Unique Links
  13. 13. Presentation Posted on Slideshare.net Search: "Text Mining Using JBoss Rules"

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