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Knowledge Base Content

Knowledge Base Content. Bruce Porter, Peter Clark Ken Barker, Art Souther, John Thompson James Fan, Dan Tecuci, Peter Yeh Marwan Elrakabawy, Sarah Tierney. Knowledge Base Content. Generic components Composition methods Simulation methods Domain-specific components Extended scenarios.

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Knowledge Base Content

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  1. Knowledge Base Content Bruce Porter, Peter Clark Ken Barker, Art Souther, John Thompson James Fan, Dan Tecuci, Peter Yeh Marwan Elrakabawy, Sarah Tierney

  2. Knowledge Base Content • Generic components • Composition methods • Simulation methods • Domain-specific components • Extended scenarios http://www.cs.utexas.edu/users/mfkb/RKF

  3. What’s in a Component? • The specification gives the definition, slot constraints, and links to standard linguistic sources. Here’s an example. • The KM code gives the axioms and an explicit interface to the user. Here’s an example. Note that the code includes only local axioms; KM infers the rest. http://www.cs.utexas.edu/users/mfkb/RKF

  4. Our Process for Building a Component • form initial clusters of actions (e.g. transfer) based on an analysis of Alberts, Roget’s clusters, Cyc, and other linguistic sources. • write a specification for each action. • search Alberts for all occurrences (including all morphological variants) of each action, and make sure that the representation will accommodate them. Here’s the result of analyzing the actions in one chapter. These “coded examples”will be useful for training SME’s. • organize the actions taxonomically and pull out commonalities that can be handled with various types of composition.* • code the actions in KM along with simple test cases, commit them to the CVS-managed library, and run all test cases daily. Larger scenarios provide the next level: integration testing.* * These points will be elaborated below.

  5. How do Components Compose? • inheritance • clichés • utility concepts • modeling

  6. Non-taxonomic composition:Clichés • a cliché is a small pattern of axioms that recurs throughout the hierarchy. For example: • Reflexive: requiredslot: agent, object agent=object • Reciprocal:requiredslot: agent, object agent is object of an instance of this action having this object as agent • Undo(A): precondition: object is the object of the resulting-state of action A postcondition: object is no longer the object of the resulting-state of action A

  7. Non-taxonomic composition:Utility Concepts • concepts that have natural homes within the hierarchy, but also form a part of the semantics of concepts across the hierarchy • Copy: • reasonable as a standalone concept • also part of Transcribe, Forge, Encode, Reproduce, etc.

  8. Non-taxonomic composition:model-as • Many concepts in the KB are “role concepts” • e.g., container, nutrient • aregeneric • are highly reusable(can be applied in many concepts) • “If the DNA containing the 5S rRNA genes is …” • “many DNA sequences produce two or more distinct proteins” • “The DNA guides the synthesis of specific RNA molecules…” • “The DNA is enclosed in …” • “The idea that DNA transfers information…” • By separating the “model” (e.g. container) and its application (e.g. to DNA), we can apply & reuse the same model in many ways.

  9. Applying models Cell generalizations: Container Consumer …? • Traditional: “Hard-wire” models to the modeled things • Better: Define machine-selectable “views” Cell model-as: Container (wall = membrane, ..) Consumer (consumes = organic molecules, ..) Vehicle (transported = DNA, …) …. • Control when and how components apply • Allows generic components to be used multiple ways (more reuse) - difficult in the traditional approach!

  10. object the-container Entity Move-Out-Of source path Portal is-between destination object instrument Be-Blocked object implies Be-Closed A Role Concept: Container Container location has-part Place is-inside Wall Place has-part Place is-outside Portal-Covering

  11. Example of Composition “eucaryotic mRNA exits the cell nucleus” • composition triggered automatically through Exit • inheritance • location of mRNA changes from inside nucleus to outside • cliché • mRNA is the mover and the moved (Exit is reflexive) • modeling • cell nucleus as a container • has an inside, an outside, a wall, portals, etc.

  12. object the-container Entity Move-Out-Of Container source path location Place has-part is-inside Wall Portal Place is-between destination has-part Place is-outside Portal-Covering Example Exit

  13. Example Eucaryotic-MRNA Exit the-container object source path Entity Container location Place has-part is-inside Wall Portal Place is-between destination has-part Place is-outside Portal-Covering

  14. Nuclear-Envelope agent has-part Cell-Nucleus Example object Eucaryotic-MRNA Exit the-container source path Container location Place has-part is-inside Wall Portal Place is-between destination has-part Place is-outside Portal-Covering

  15. Nuclear-Envelope has-part Example agent object the-container Eucaryotic-MRNA Exit Cell-Nucleus source path has-part location Place is-inside Wall Portal Place is-between destination has-part Place is-outside Portal-Covering

  16. Example Nuclear-Envelope agent has-part object the-container Eucaryotic-MRNA Exit Cell-Nucleus source path location Place is-inside Portal Place is-between destination has-part Place is-outside Portal-Covering

  17. G A S1 S2 S3 S1.1 S1.2 Answering Questions via Simulation • To reason about change over time, KM builds a graph of actions and states Global contains time- invariant descriptions Action A transforms State1 into State2 S3 describes ‘the world’ during A These states show S1 ‘under a microscope’ • KM’s simulation is discrete, and we’re using KM • just for normative models. We’re integrating KM with • Cohen’s continuous simulators to handle other models.

  18. Pump-Priming Knowledge • Our goals for pump priming: • Define the terms used in chapter 7, but introduced earlier • Provide the ‘common sense’ knowledge that motivates the process of protein synthesis • Our approach is to develop: • Partonomies and taxonomies for entities and processes • Numerous scenarios related to protein synthesis

  19. Example Scenarios • The role of proteins in cell metabolism • The overall function of cells and how the functions are affected by protein synthesis • The role of protein synthesis in cell adaptation • The role of primary and secondary structure • Enzyme kinetics, diffusion, bonding, and energy coupling

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