Case Studies
IoT & Mobile
Problem:
Video infrastructure client needs very small models for mobile devices
The Data:
16K instances; 107 features; 2 classes
Result:
The Cancer Genome Atlas
View Graph
Problem:
We use Brainome to identify genes that are consistently over-expressed in different tumor types
The Data:
21,000 gene expressions for patients with 33 different types of cancer and a sample set of healthy patients combined into a 11,000 row, 21,000 column, 34 class table
Result:
Brainome model achieves 90% accuracy in predicting cancer type based on over expression of specific genes
Genotype-Tissue Expression
Problem:
We use Brainome to classify tissue types based on RNA seq-data
The Data:
16K observations; 56K features (genes); 21 classes
Result:
*Run on 48 Core AMD Ryzen 3960X, 128 GB RAM
Microbiome research
Problem:
Identify predictors of inflammatory bowel disease (IBD)
The Data:
1,627 observations; 71,266 features; 2 classes (healthy vs IBD)
Result:
*Data set analyzed using Dell XPS-13 laptop, Intel i7 CPU 3 GHz, 32 GB RAM, 2 TB SSD
Theoretical physics
View Chart
Problem:
Rework of 2014 model published in Nature Communications:
The Data:
5 million observations; 18 features; 2 classes
