Code for Gomez Lab at UNC-Chapel Hill

EMBER

cd_postop

colorectal_predictors

Code to accompany colorectal surgery outcome predictors manuscripts

cvsm

Computer vision for specimen mammography

kinotype_viability

Code related to constructing and testing models for cell viability

nsqip_procedurespecific

Predict procedure specific outcomes from the NSQIP database using neural networks and logistic regression

PDACperturbations

Data and code associated with pancreatic cancer drug screening and modeling

ped_ibd_rnaseq

xCEED

xCEED: Methods for the comparison of phylogenetic trees

bryant_optimization

code to expedite fluorescence data analysis

exit

Code used in the EXIT paper for sequence processing/analysis.

genie

code to download/prep genie data

invado_population

Quantification of Invadopodia activity in cell populations

kinase_inhibitor_pred_app

Shiny application for predicting kinase inhibitor effects on cell viability

kinotypeClusteringAndRegression

Joint Repository of GR Metrics Regression and Kinase Interaction Network (KIN) Clustering

liver-glycogen-model

Code from the paper: Xu K, Morgan KT, Todd A, Elston TC and Gomez SM. A whole-body model for glycogen regulation reveals a critical role for substrate cycling in maintaining blood glucose homeostasis. PLoS Computational Biology. 2011. Dec;7(12):e1002272.

MBSAQIP_READMISSION

Using ML to predict readmission following bariatric surgery

MiscViz

Visualizations and JavaScript objects for the GomezLab

single_invado_analysis

Quantitative Analysis of Single Invadopodia

subnetclustering

cali_analysis

Software for the Analysis of the Effects of CALI Before/After Experiments Around the Cell Edge

focal_adhesions

Software for the Analysis of Focal Adhesion Images

kinomescan_viability_prediction

Code for processing kinomescan data for cell viability prediction

kinotype_combination_prediction

network-viz

network_vis_webapp

PTEN_null_essential

Code for searching a few databases for apparent essential pairs in cancer data

segnet

segNET is a suite of tools for identifying gene modules from complex genome-wide networks