Ontological%20Model%20for%20Colon%20Carcinoma:%20A%20Case%20Study%20for%20Knowledge%20Representation%20in%20Clinical%20Bioinformatics - PowerPoint PPT Presentation

About This Presentation
Title:

Ontological%20Model%20for%20Colon%20Carcinoma:%20A%20Case%20Study%20for%20Knowledge%20Representation%20in%20Clinical%20Bioinformatics

Description:

Title: Caveats on Knowledge Discovery and Data Mining (KDDM) for Bio-Terrorism Detection Author: Powerpt Last modified by: Barry Smith Created Date – PowerPoint PPT presentation

Number of Views:137
Avg rating:3.0/5.0

less

Transcript and Presenter's Notes

Title: Ontological%20Model%20for%20Colon%20Carcinoma:%20A%20Case%20Study%20for%20Knowledge%20Representation%20in%20Clinical%20Bioinformatics


1
Ontological Model for Colon Carcinoma A Case
Study for Knowledge Representation in Clinical
Bioinformatics
O N C O L O G Y O N T O L O G Y
  • Kumar A1,2, Yip L3, Jaremek M2, Scheib H3
  • 1IFOMIS, University of Saarland, Germany
  • 2Ludwig-Maximilians Universität, München, Germany
  • 3Swiss Institute for Bioinformatics, Geneva,
    Switzerland

2
How the two worlds meet?
O N C O L O G Y O N T O L O G Y
Clinical
Specific disease topics E-Health, Health support
system Patient Management Patient health education
?
Molecular Biology
Biomedical Information on the Web Swiss-Prot,
Swiss-Prot Variant pages Proteins, mutations,
functions and structures
3
How the two worlds meet?
O N C O L O G Y O N T O L O G Y
  • Diseases
  • Pathological Processes
  • Body site for diseases
  • Diseases by staging
  • Risk factors

SNOMED
  • Anatomy
  • Is-a, part-of
  • Granular relationship

FMA
  • Biological Processes
  • Ontology
  • Classification

GO
  • Swiss-Prot proteins
  • Annotation function, structure, mutation

4
How the two worlds meet?
O N C O L O G Y O N T O L O G Y
Disease schema
Protein 3D models
Swiss-Prot entries
ModSNP database
5
What is Protégé?
O N C O L O G Y O N T O L O G Y
  • Frame based system Allows formation of
    class-subclass relations, provides support for
    other relations between classes, compatible with
    OWL, XML, database standards
  • Support for various types of visualizations
    Graphical, Web-based
  • Support for import/export
  • Support for reasoning Description Logic based
  • Can give outputs in various formats
  • Difficulties with input

6
Disease Representation
O N C O L O G Y O N T O L O G Y
  • Disease classification based on Snomed CT
  • Various aspects considered for classification
    (currently present in the form of multiple
    inheritance)
  • Added from textbooks (deVita Principles of
    Oncology and Harrison Principles of Internal
    medicine)
  • Staging of diseases (TNM, Dukes, Modified
    Asler-Coller)
  • Screening (Patients screened based on their level
    of risk)
  • Risk factors
  • Localization
  • Pathology
  • To be added Pharmacotherapeutics, Symptoms and
    Signs

7
Anatomical and Histological Representation
O N C O L O G Y O N T O L O G Y
  • Anatomy of colon represented at Organ system,
    Organ, Tissue, Cell and Subcellular levels of
    granularity (Foundational Model of Anatomy)
  • Gene Ontologys Cellular Component axis situated
    within the FMA axis
  • Gross pathology mapped to the Carcinoma location
  • Information regarding Clinical procedures,
    Carcinoma extent, Vascular invasion, Histological
    pathology being added
  • Extensions being done to add relations like
    is-located-in, is-surrounded-by, etc. to make the
    anatomical representation deducible

8
Interlink between disease, LocusLink, Swiss-Prot,
GO annotations
O N C O L O G Y O N T O L O G Y
Colon cancer/Colon carcinoma
LocusLink
SwissProt
Gene Ontology
9
Gene Ontology
O N C O L O G Y O N T O L O G Y
  • Association rules found considering the Gene
    Ontology annotations of SWISSPROT proteins
  • Gene Ontology consists of three axes
  • Cellular Component
  • Molecular Function
  • Biological Processes
  • Association between GO terms were established on
    the basis of these annotations
  • Database-based approach
  • Apriori-algorithm based approach
  • Dependency relations based on POS tagger

10
Levels of granularity
O N C O L O G Y O N T O L O G Y
  • Levels of granularity in human body
  • Organism
  • Organ system
  • Cardinal body parts
  • Organ
  • Organ part
  • Tissues
  • Cells
  • Subcellular organelles
  • Molecules
  • Atoms
  • Fundamentals behind the levels of granularity
  • Grains, Structure, Origin

11
Results
O N C O L O G Y O N T O L O G Y
12
Results (Apriori)
O N C O L O G Y O N T O L O G Y
  • Support and Confidence are defined
  • ribosome lt- ribosome biogenesis protein
    biosynthesis (0.2, 93.2)
  • This rule says that there are 0.2 of the total
    annotations, put together ribosome biogenesis and
    protein biosynthesis, of which 93.2 (i.e. 82)
    are also annotated with the term ribosome.
  • Formal ontological relationsapplied between the
    entities, which would help to have deductions
    has spatial projection, processual part of,
    facilitates, mediates, perpetrates

13
Relations to biological pathways
O N C O L O G Y O N T O L O G Y
  • Pathway resources KEGG, PATH, GenePath
  • Protein interaction database resources DIP,
    BIND, PiP, IntAct
  • Links to these databases possible through
    Swissprot and GO annotations
  • Associations found within GO annotations parallel
    the pathways and protein interactions (under
    verification)
  • Text mining resources being considered

14
Ontological Model for Colon Carcinoma A Case
Study for Knowledge Representation in Clinical
Bioinformatics
O N C O L O G Y O N T O L O G Y
  • Kumar A1,2, Yip L3, Jaremek M2, Scheib H3
  • 1IFOMIS, University of Saarland, Germany
  • 2Ludwig-Maximilians Universität, München, Germany
  • 3Swiss Institute for Bioinformatics, Geneva,
    Switzerland
Write a Comment
User Comments (0)
About PowerShow.com