data driven decision making ryan ramanujam … · dr. pierre dönnes - phd in bioinformatics -...
TRANSCRIPT
Current methods: Machine learning, AI, classical statistics
Often insufficient to analyze data due to noise, inaccurate measurements
DATAVERGE PIPELINE
Data Sources ETL GEODE REPORTS
Li et al. Sci Transl Med (2015)
TOPOLOGICAL DATA ANALYSIS
INDUSTRIES
Life Sciences – how can treatments be optimized for cancer
patients?
Finance – which factors influence predictive currency
exchange rates?
Manufacturing/production – which car parts fail early and
under which conditions?
Marketing/sales – which products and strategies will boost
sales?
GEOMETRIC DATA EXPLORER (GEODE)
Pre-processing
Data partitioning
Comparison of expression data from gastric cancer
- Hippo, et. Al. “Global Gene Expression Analysis of Gastric Cancer by
Oligonucleotide Microarrays”. Cancer Research (2002)
n=30, 22 gastric cancer tissues and 8 noncancerous tissue
6936 genes measured
Goals:
1) Correctly classify samples (cross-validation)
2) Determine which genes have highest correlation with disease status
3) Generate subgroups for doctors to determine best patient treatment
GASTRIC CANCER EXAMPLE
GEO GRAPHING
Prediction accuracy: GEODE 94.8%
SVM classifier 72.4%
GEO SIGNATURES
Subgroup 1• Gene X05276_at upregulated
• Gene X12791_at downregulared
Subgroup 2• Gene K01396_at upregulated
• Gene D14663_at upregulated
• Gene U90426_at upregulated
Subgroup 3• Gene M33308_at downregulated
• Gene X14008_rna1_f_at downregulated
GASTRIC CANCER EXAMPLE
DATAVERGE USE CASE
Stage 1 – Customer interaction
DATAVERGE USE CASE
Stage 2 – GEODE Analysis
DATAVERGE USE CASE
Stage 2 – GEODE Analysis
DATAVERGE USE CASE
Stage 2 – GEODE Analysis
Model building
DATAVERGE USE CASE
Stage 3 – Reporting
DATAVERGE USE CASE
Stage 3 – Reporting
Dr. Ryan Ramanujam- Associate Prof. Karolinska Institutet, Researcher KTH
- MBA IE Business School, 23 biomedical publications
Dr. Pierre Dönnes- PhD in Bioinformatics
- Established business development record in big pharma
Prof. Wojciech Chachólski- Professor, KTH Dept. of Mathematics
- World leading expert in algebraic topology
DATAVERGE TEAM
We provide new ways to analyze data, giving better
accuracy and interpretation of results
The underlying algorithms are based on research done
at KTH and Karolinska Institutet
Early support provided by the KTH Innovation office
and a 2017 VINNOVA Innovation Startup Grant
We are looking for partners who want to fully harness the
power of their data
DATAVERGE SUMMARY
