Charles A. Blatti

The paper identifies transcriptional network disruptions in drug-resistant prostate cancer using TraRe, uncovering key regulatory modules and transcription factors associated with resistance.

The paper identifies brain gene regulatory network plasticity as a mechanism underlying individual differences in honey bee behavior.

GENVISAGE identifies discriminative gene pairs in genomic data and visualizes their separation between biological classes with a 400X speedup over baselines.

This study compares module-based and single gene methods for gene regulatory network inference, finding that a variational Bayes approach outperforms existing methods in both simulated and real data.

This paper introduces GeneSet MAPR, a supervised learning algorithm for gene set analysis that leverages network patterns to improve identification of genes related to a given gene set, outperforming existing methods.

The paper presents a draft genome assembly of the alkali bee and identifies genes under selection and population genetic patterns.

The paper identifies conserved neurogenomic response toolkits across species using multi-species transcriptomic analysis and systems-level functional grouping.