MINING FOR MEANING: Data mining & Knowledge extraction Laboratory of Parasitic Diseases, NIAID

Knowledge Experiment Results Data interpretation Conclusions

Experiment Results Knowledge Conclusions High publication rates Knowledge Data interpretation

Experiment Results Knowledge Conclusions High publication rates Knowledge High-throughput screening Results Data interpretation

Experiment Results Knowledge Conclusions Knowledge Results GENE EXPRESSION PROFILING Identify relevant genes Identify expression patterns Data interpretation

Experiment Results Knowledge Conclusions Knowledge GENE EXPRESSION PROFILING FUNCTIONAL PROFILING Identify relevant genes Identify expression patterns Identify functional implications Data interpretation

FUNCTIONAL PROFILING MINING FOR MEANING:

ProtozoanBacteriavs Leishmania Mycobacterium tuberculosis Leishmania majorLeishmania donovanivs Brugia malayi Toxoplasma gondii Elutriated Human Monocytes IntracellularExtracellular vs 7 donors Infection with 5 pathogens -overnight- DC IL-4 + GM-CSF Mac M-CSF RNA pools RNA pools U95

Dataset DC genesExtraction  75 Gene expression profiling  Filter 1200 Dataset Mac

DC Pathogens Genes Fold Change (log2) Lm Ld Tg Bm 50 Bm 5 Mtb Fold Change (log2) Induced by intracellular pathogens Leishmania & TB Toxoplasma & TB Toxoplasma

FUNCTIONAL PROFILING MINING FOR MEANING: WITH GENE ONTOLOGIES - GO

FUNCTIONAL PROFILING MINING FOR MEANING: WITH GENE ONTOLOGIES - GO WITH LITERATURE ONTOLOGIES - MESH

FUNCTIONAL PROFILING MINING FOR MEANING: WITH GENE ONTOLOGIES - GO WITH LITERATURE ONTOLOGIES - MESH WITH LITERATURE ABSTRACTS

Experiment Results Knowledge Conclusions Knowledge Data interpretation 12 million references

Experiment Results Knowledge Conclusions Knowledge Results Data interpretation 12 million references

FUNCTIONAL PROFILING MINING FOR MEANING: WITH LITERATURE ABSTRACTS  Co-citation Network

FUNCTIONAL PROFILING MINING FOR MEANING: WITH LITERATURE ABSTRACTS  Co-citation Network  Natural Language Processing

FUNCTIONAL PROFILING MINING FOR MEANING: WITH LITERATURE ABSTRACTS  Co-citation Network  Natural Language Processing  L LL Literature Profiling

Select relevant terms Determine term occurrence in abstracts Retrieve relevant literature for each gene Gene A Gene B Gene C… Gene X 1.Gene - Literature indexation 3.Term filtering DiscriminationCo-occurrence Analyze functional relationships 2. Analysis of abstract contents Abstracts Term occurrences in abstracts

KNOWLEDGE 12 million references Experimental system Gene List - Translate genelists into keywords - Interpret data - Identify functional relationships

FUNCTIONAL PROFILING MINING FOR MEANING: LITERATURE MINING

Experiment Results Knowledge Conclusions High publication rates Knowledge Data interpretation

DATA MINING LITERATURE MINING MINING FOR MEANING: DOCUMENT CLUSTERING

DATA MINING LITERATURE MINING MINING FOR MEANING: DOCUMENT CLUSTERING NLP

DATA MINING LITERATURE MINING MINING FOR MEANING: DOCUMENT CLUSTERING NLP LITERATURE PROFILING

Experiment Results Knowledge Conclusions Knowledge Results GENE EXPRESSION PROFILING Identify relevant genes Identify expression patterns Data interpretation