Sem antics-based m odel discovery ( and assem bly) for renal - - PowerPoint PPT Presentation

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Sem antics-based m odel discovery ( and assem bly) for renal transport Dew an Sarw ar , Reza Kalbasi, Koray Atalag, David Nickerson Auckland Bioengineering Institute University of Auckland, New Zealand https: / / doi.org/ 10.17608/

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Sem antics-based m odel discovery ( and assem bly) for renal transport

Dew an Sarw ar, Reza Kalbasi, Koray Atalag, David Nickerson Auckland Bioengineering Institute University of Auckland, New Zealand https: / / doi.org/ 10.17608/ k6.auckland.7199834

Boston October 2 0 1 8

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Motivation

  • Given a collection of mechanisms and/ or observations, e.g.,

– electrophysiology measurements – imaging data – diseases (SNOMED-CT, ICD, Human Disease Ontology...) – drug actions – clinical observations (openEHR archetypes) – etc…

  • can we extract a model from the Physiome Model Repository suitable for

testing clinical or experimental hypotheses?

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Client/PC Cloud/Server

OpenCOR

  • create/edit models
  • singular annotation of model entities
  • create/edit simulation experiments
  • execute simulation experiments

Physiom e Repository ( PMR) W orkspace

EBI Ontology Lookup Service

Gives permanent URLs to workspace content, e.g.,

  • https://models.physiomeproject.org/w/…/model.xml
  • https://models.physiomeproject.org/w/…/sedml.xml

Sem Gen

  • annotate, merge and decompose models
  • singular, composite and human readable

annotation of model entities

W eb services: a) W SDbfetch b) Clustal Om ega

Epithelial Modelling Platform

Step

1. Search/discover epithelial transport models 2. Query OLS to map human-readable names from reference ontology URIs 3. Load discovered models 4. Analyze similarity of models 5. Semantically display models on the Platform for visualization and graphical editing 6. Recommender system to guide model composition 7. Send suggested protein models, i.e. protein IDs, in the recommender system to EBI in

  • rder to retrieve a matrix score for ranking

ChEBI FMA GO OPB PATO SBO SNOMEDCT

Local copy of w orkspace

Model editing & simulation Model annotation

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  • Comprehensive descriptions of the underlying

anatomical connectivity across multiple renal scales are being mapped to the biologically- meaningful variables in each of the model.

  • UniProt identifiers, FMA terms, variables biological

meaning, species used, etc.

Kidney Model Annotation

Renal SGLT1 model

Protein: Sodium/glucose cotransporter 1 (SGLT1) UniProt ID: P11170 Gene: SLC5A1 Species: Oryctolagus cuniculus (Rabbit) Located in:

  • Proximal convoluted tubule (FMA:17693)
  • Apical plasma membrane (FMA:84666)
  • Epithelial cell of proximal tubule (FMA:70973)
  • Proximal straight tubule (FMA:17716)
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  • NHE3 : S1, S2, SDL,

LDLOM, tAL, mTAL, cTAL, DCT

  • SGLT1 : cTAL
  • TSC: S1, S2, cTAL,

DCT

  • SGLT2 : Not exist

Exam ple source of know ledge

RNA-seq I dentification of Transcripts Expressed along the Renal Tubule

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Sem Gen Annotator I nterface

Illustrative example of SemGen annotator interface of the Weinstein model where codewords identifies CellML variables and annotates flux of sodium from luminal compartment to cytosol compartment through sodium/ hydrogen exchanger 3.

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Epithelial Modelling Platform

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Epithelial Modelling Platform

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Epithelial Modelling Platform

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Epithelial Modelling Platform

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Epithelial Modelling Platform

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Current status

  • Model discovery demonstration: https: / / github.com/ dewancse/ model-

discovery-tool

  • Epithelial modelling platform: https: / / github.com/ dewancse/ epithelial-

modelling-platform

  • Implementing model composition service
  • Extending model similarity to simulation experiment similarity to automate

model “verification”

  • Future work: language processing to translate user requirements into

semantic queries.

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  • Tommy Yu @ ABI
  • John Gennari, Max Neal, Graham Kim @ University of Washington
  • Brian Carlson @ University of Michigan

Aotearoa Foundation

Acknow ledgem ents

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