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BioAssay Ontology (BAO ). chemical biology. PubChem. domain. caspase activity. standards. cheminformatics. nomenclature. activity. semantic. enzyme reporter. fluorescence. viability. binding based. programming. data sets. knowledge. search. screening. technology. end point.

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bioassay ontology bao
BioAssay Ontology (BAO)

chemical biology

PubChem

domain

caspase activity

standards

cheminformatics

nomenclature

activity

semantic

enzyme reporter

fluorescence

viability

binding based

programming

data sets

knowledge

search

screening

technology

end point

PDSP

thesauri

article

object

XML

enzyme substrate based

versioning

high-thoughput screening (HTS)

natural language

software

classification

polysemes

biological pathways

Beta-Lactamase Induction

dehydrogenase activity

specificity

annotation

subject indexing schemes

properties

GFP induction

Fluorogenic substrate

Stephan Schürer, PhD

ChemBank

chemical probes

information exchange

servers

ATP Luciferin Coupled

classes

synonyms

search tool

controlled vocabulary

ICBO, Buffalo, July 30 2011

biological assay

disease networks

biomedical knowledge

structure

concepts

meta-data

taxonomies

small molecule

subject headings

cyclic AMP redistribution

RDF

calcium redistribution

sschurer@med.miami.edu

OWL

novel chemical tools

indexing

pharmaceutical

semantic web

library

authorized terms

structural biology

individuals

homographs

tags

energy transfer

slide2

Background for BioAssayOntology

High-throughput screening

  • One of the most important approaches to find novel entry points for drug discovery programs
  • Historically in pharmaceutical companies
  • Since ~2005, massive NIH effort (MLI) to make HTS accessible to public sector research
  • PubChem is the major repository of HTS data
  • More recently: EU-OpenScreen project
slide3

Motivation for BioAssayOntology

Large public screening data sets

PubChem, ChEMBL, PDSP, ChemBank, Binding DB

  • Lack of standardized assay annotations
  • No standardized endpoint names or formats
  • Data is rarely re-used(!)
  • Common queries cannot be asked
  • Analysis across different data sets is difficult
  • Integration with other databases is difficult
  • No knowledge model for assays and screening results
slide4

Queries the Ontology should be able to answer

Identify inhibitors of kinases in biochemical assays.

Identify compounds active in multiple luciferase reporter gene assays.

Identify compounds active in cell viability assays and organize by cell lines and assay types.

Identify active compounds in assays related to pathway X.

slide5

Leverage the aggregated corpus of publically available HTS data to infer molecular mechanism of actions (MMOA) of small molecule perturbagensin biological model systems.

Schüreret al. “BioAssay Ontology Annotations Facilitate Cross-Analysis of Diverse High-throughput Screening Data Sets” J Biomol Screen2011 (16), 415-426.

slide6

BAO Products and Resources

  • BAOSearch Software (beta):http://baosearch.ccs.miami.edu
    • Query, explore, download BAO-annotated PubChem content
    • Some semantic search capabilities
  • Project Website and Wiki with relevant materials and documentation:http://www.bioassayontology.org/http://www.bioassayontology.org/wiki
slide7

Questions / Discussion points

  • Application / user focus vs. “universal” ontologies
    • Efficiency vs. “realism” of representations
    • Rapid application development
  • Orthogonal ontologies vs. Ontology mapping
  • Universal “realism” vs. domain or application-specific
    • Chemical bond: 2D structure graph, 3D rule based, molecular mechanics, semi-empirical, up-initio QM
    • Disease
    • Virtual world
slide8

Questions / Discussion points

  • Collaborative ontology development
    • Collaborative vs. individual effort
    • Control over development and focus / application focus
    • Rapid application development
    • Quality
  • Aligning BAO to upper level ontology (BFO)
    • Benefits vs. required resources
    • Do upper level ontologies matter for specialized applications?
slide9

Questions / Discussion points

  • Aligning BAO with OBI
    • Some level of overlap
    • OBI: process-oriented (model the investigation)
    • BAO: purpose of categorization and analysis of HTS data
    • BAO model becomes more complex if based on OBI
  • How do we do it practically
    • Define missing assays to OBI and MIREOT back?
    • Quick term templates (QTT)?
    • Define our relations as short-cut relationships (using RO)?
slide11

BAO-facilitated Example for Analysis

(Luciferase Assays)

Details in: Schürer et al. “BioAssay Ontology Annotations Facilitate Cross-Analysis of Diverse High-throughput Screening Data Sets” J Biomol Screen2011 (16), 415-426.

slide12

Most promiscuous reporter gene compounds

Assay Count

Panel Assay

Single Conc

Other

Conc-response

slide13

Luciferase Enzyme Inhibitors

  • Generally cytotoxic

Most promiscuous reporter gene compounds

Compounds

Promiscuity Index

1

0

0.2

ATP SC

ATP DR

Viability SC

Viability DR

Luciferin SC

Luciferin DR

Reporter SC

Reporter DR

Enz Activ SC

Enz Activ DR

slide14

Examples: Cytotoxic Series

Daunorubicin

Cluster Reporter PCIdx: 0.56

Cluster Reporter Active: 58

Cluster Viability PCIdx: 0.64

Cluster Viability Active 27

Cluster Reporter PCIdx: 0.48

Cluster Reporter Active: 23

Cluster Viability PCIdx: 0.45

Cluster Viability Active 10

Emetine

Cluster Reporter PCIdx: 0.41

Cluster Reporter Active: 29

Cluster Viability PCIdx: 0.57

Cluster Viability Active 13

slide15

Examples: Luciferase Inhibitor Series

Cluster Size: 6

Cluster Reporter PCIdx: 0.61

Cluster Reporter Active: 101

Cluster EnzActivity PCIdx: 0.58

Cluster EnzActivity: 15

Cluster Size: 5

Cluster Reporter PCIdx: 0.46

Cluster Reporter Active: 77

Cluster EnzActivity PCIdx: 0.58

Cluster EnzActivity: 14

Cluster Size: 4

Cluster Reporter PCIdx: 0.38

Cluster Reporter Active: 52

Cluster EnzActivityPCIdx: 0.61

Cluster EnzActivity: 11

Schürer et al. “BioAssay Ontology Annotations Facilitate Cross-Analysis of Diverse High-throughput Screening Data Sets” J Biomol Screen2011(16), 415-426.

slide16

BAO Project: Three major components

  • Development of the Bioassay Ontology
  • Annotation of assays and assay results(content curation)
  • Development of software tools
slide24

BAO Products and Resources

  • BioAssayOntology (NCBO bioportal and project site):http://bioportal.bioontology.org/ontologies/45410http://www.bioassayontology.org/visualize/
  • Terminology / annotations for biochemical assays: http://www.bioassayontology.org/>Assay Annotation Template
  • Over 1000 BAO-annotated assays from PubChem (available in BAOSearch)
slide25

Acknowledgements

  • SamindaAbeyruwan
  • Uma Vempati
  • Magdalena Przydzial
  • KunieSakurai
  • Robin Smith
  • YuanyuanJia
  • Caty Chung
  • Chris Mader
  • AmarKoleti
  • NakulDatar
  • SreeharshaVenkatapuram
  • FelimonGayanilo
  • Mark Southern
  • UbboVisser
  • Vance Lemmon
  • MitsunoriOgihara
  • Nick Tsinoremas

http://bioassayontology.org

sschurer@med.miami.edu