Next generation semantic support technology

CD40 ligand and tumor necrosis factor alpha, the cells acquire a mature phenotype of dendritic cells that is characterized by up-regulation of human leukocy

te antigen (CD80, CD86, CD40and CD54 and appearance of CD83. These

What we are NOT

• A Search Engine

• A Pathway Tool

• An Annotated Database

What do we do ?

• Disambiguate Text

• Meta-analyse at concept level

• Provide meta-analysed information

• Support Information Based Knowledge Discovery (especially new associations)

Ambiguity 1: Synonyms

• Facilitating networks of information. van Mulligen EM, Diwersy M, Schmidt M, Buurman H, Mons BProceedings of AMIA Symposium 2000, 868-72

Ambiguity 2: Homonyms

PSAProstate Specific AntigenPSoriatic Arthritisalpha-2,8-PolySialic AcidPolySubstance AbusePicryl Sulfonic AcidPolymeric Silicic AcidPartial Sensory AgnosiaPoultry Science Association

• Distribution of information in biomedical abstracts and full-text publications, Schuemie MJ, Weeber M, Schijvenaars BJ, van Mulligen EM, van der Eijk CC, Jelier R, Mons B, Kors JA, Bioinformatics 2004 Nov 1, 20:2597-604

The Knowlet

• Contextual annotation of web pages for interactive browsing, van Mulligen E, Diwersy M, Schijvenaars B, Weeber M, van der Eijk CC, Jelier R, Schuemie M, Kors J, Mons B, Medinfo 2004, 11:94-8• Which gene did you mean?, Mons B, BMC Bioinformatics 2005 Jun 7, 6:142

Creating Reference Knowlets

PSA Prostate Specific Antigen

PSA Psoriatic Arthritis

ReferenceKnowlet

ReferenceKnowlet

Context matching

PSA ??

Prostate Specific Antigen

Psoriatic Arthritis

ReferenceKnowlet

ReferenceKnowlet

New text

93 % correct in ‘Worst Case Scenario’98 % overall….

• Thesaurus-based disambiguation of gene symbols. Schijvenaars BJ, Mons B, Weeber M, Schuemie MJ, van Mulligen EM, Wain HM, Kors JABMC Bioinformatics 2005 Jun 16, 6:149•Word sense disambiguation in the biomedical domain: an overview. Schuemie MJ, Kors JA, Mons B, Journal of Computational Biology 2005 Jun, 12:554-65

x

person organisation Object 1

gene

Object 2

disease

Object 3

drug

> 15 million Knowlets from PubMed etc.

Building an association matrix of large data sources

 

0

16 0

30 3 0

28 35 20 0

188 4 15 13 0

A matrix of associative distances

meta-analysis

HierarchicalClusteringACSMDSEtc.

Meta-analysis 1: ACS

• Constructing an Associative Concept Space for Literature-based Discovery, van der Eijk CC, van Mulligen EM, Kors JA, Mons B, van den Berg JJournal of the American Society for Information Science and Technology 2004, 55(5): 436-444•Co-occurrence based meta-analysis of scientific texts: retrieving biological relationships between genes. Jelier R, Jenster G, Dorssers LC, van der Eijk CC, •van Mulligen EM, Mons B, Kors JA Bioinformatics 2005 May 1, 21:2049-58

Meta Analysis 2: Multidimensional Scaling (MDS)

• Paper in co-authorship with SIB and GeneBio/SwissProt in preparation by M. Scheumie and Christine Chicester.

> 700 proteins from the Nucleolus, re-annotated……….and more…..

Meta Analysis 2: Hierarchical Clustering

200779_at200799_at200800_s_at201000_at201427_s_at201939_at202022_at202887_s_at203355_s_at203574_at203622_s_at204026_s_at204033_at204146_at204285_s_at204415_at205047_s_at205239_at208763_s_at208813_at208949_s_at209230_s_at209608_s_at210338_s_at212063_at212501_at212971_at213040_s_at213075_at213703_at217999_s_at218145_at218180_s_at218585_s_at218986_s_at219588_s_at219961_s_at221731_x_at222039_at222111_at35820_at

Q-norm

Q-norm

Q-norm

Physiology  Phosphorylation  Lymphocyte Transformation  Cell Cycle

Anatomy  Cells  T-Lymphocytes  Dendritic Cells  Monocytes  Lymph Nodes  Cell Line

  Blood Platelets

Anatomy  T-Lymphocytes  Macrophages  Cells  Cell Line  Fibroblasts  Monocytes  Neutrophils

 Immunity, Natural  Genotype  Transfection  Antigen Presentation  Genetic Predisposition to Disease  Fibrinolysis

2004----2005

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

textmining

PLEASE !

Writing =ambiguity

Future (hope)

Papyrust

But….. journal editors who publish scientific studies and grant institutions that fund them very often see less value in efforts to build and analyze scientific databases than in old-fashioned experiments