Computational inference of cancer-specific vulnerabilities in clinical samples (Genome Biology 2020)


- Source codesGitHub link to codes for DeepDependency
- Regulatory networks* BayesianReal breast Shuffled breast Inverted breast Liver* ARACNeReal breast Shuffled breast Inverted breast Liver
- Sample dataCellline basal Bayesian Cellline basal ARACNe Model input Clinical samples
- Prediction resultsTumor-specific dependencies for TCGA samples

Predicting clinical benefit of immunotherapy by antigenic or functional mutation affecting tumor immunogenicity (Nature Communications 2020)


- Source codesPeptide-MHC binding prediction by CNN

DNA methylation loss promotes immune evasion of tumors with high mutation and copy number load (Nature Communications 2019)


Methylation raw data (Idat files)
Methylation metadata worksheet

Convolutional neural network model to predict causal risk factors that share complex regulatory features (Nucleic Acids Research 2019)


GitHub link to codes for cnnGWAS
Feature datasets (DHS, histone modification, pathway, TFBS)
Imputation results (1000 Genomes reference panel)

Network perturbation by recurrent regulatory variants in cancer (PLOS Comput Biol 2017)


- Chromatin interactomeMCF7 HepG2 K562
- NetworksBayesian causal regulatory networkARACNe transcription network (breast cancer)ARACNe transcription network (liver cancer)PCAPMI transcription network (breast cancer)PCAPMI transcription network (liver cancer)Integrated physical protein interaction networkProbabilistic functional protein association network

Global transcription network incorporating distal regulator binding reveals selective cooperation of cancer drivers and risk genes (Nucleic Acids Res 2015)


Global network
Prior framework