Daniel Jay Brat

Effects of Combination Therapy of a CDK4/6 and MEK Inhibitor in Diffuse Midline Glioma Preclinical Models

This study evaluates combination therapy of CDK4/6 and MEK inhibitors in DMG models, finding survival benefits in GEM but not PDX models.

Tumor-initiating genetics and therapy drive divergent molecular evolution in IDH-mutant gliomas

This study identifies genetic changes in IDH-mutant gliomas that correlate with treatment response and tumor evolution using longitudinal genomic data from 206 patient samples.

An integrative web-based software tool for multi-dimensional pathology whole-slide image analytics

The paper introduces DPLab, a web-based platform for analyzing whole-slide pathology images, enabling 3D tissue reconstruction and sharing of analysis results.

TASI: A software tool for spatial-temporal quantification of tumor spheroid dynamics

TASI quantifies tumor spheroid dynamics through spatiotemporal segmentation, feature extraction, modeling, and statistical analysis, demonstrating its utility in analyzing non-small cell lung cancer spheroids.

Predicting cancer outcomes from histology and genomics using convolutional networks

This study uses deep learning to predict cancer patient outcomes by integrating histology images and genomic data, showing improved performance over current clinical methods for glioma survival prediction.

Interactive Phenotyping Of Large-Scale Histology Imaging Data With HistomicsML

HistomicsML enables interactive machine learning for analyzing histology images to identify phenotypes and predict survival in gliomas.

Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models

This paper applies deep learning and Bayesian optimization to predict cancer clinical outcomes from genomic data, showing improved prognostic accuracy through transfer learning and providing an open-source framework.