Data Mining of a Remote Behavioral Tracking System for Type 2 Diabetes Patients: A Prospective Cohort Study.

Background: Complications from type 2 diabetes mellitus can be prevented when patients perform health behaviors such as vigorous exercise and glucose-regulated diet. The use of smartphones for tracking such behaviors has demonstrated success in type 2 diabetes management while generating repositories of analyzable digital data, which, when better understood, may help improve care. Data mining methods were used in this study to better understand self-monitoring patterns using smartphone tracking software.

Comparative network analysis via differential graphlet communities.

While current protein interaction data provides a rich resource for molecular biology, it mostly lacks condition-specific details. Abundance of mRNA data for most diseases provides potential to model condition-specific transcriptional changes. Transcriptional data enables modeling disease mechanisms, and in turn provide potential treatments.

Correlating CpG islands, motifs, and sequence variants in human chromosome 21.

Background: CpG islands are important regions in DNA. They usually appear at the 5' end of genes containing GC-rich dinucleotides. When DNA methylation occurs, gene regulation is affected and it sometimes leads to carcinogenesis.