Publications
Included here is a list of publications from OCG programs. All published data are available to the research community through the program-specific data matrices.
* denotes publications from the CTD2 initiative that are results of intra-Network collaborations
CTD2 scientists at UTSW employed a chemistry-first approach to map the associations between chemicals and genetic lesions in lung cancer. These chemical vulnerabilities may reveal novel druggable targets for lung cancer.
Scientists proposed a framework to investigate the genomic alterations in neuroblastoma subtypes and identified TEAD4, a transcription factor, as a novel target for therapy.
Scientists proposed a framework to investigate the genomic alterations in neuroblastoma subtypes and identified TEAD4, a transcription factor, as a novel target for therapy.
Researchers at the UCSD CTD2 Center created a parsimonious composite network (PCNet), which has high efficiency and performance over any single network.
Broad Institute CTD2 scientists developed a bioinformatic approach, RWEN, that predicts the responses of human cancer cell lines to a panel of compounds using the gene-expression profiles.
CTD2 researchers at UCSF-1 present a quantitative map linking the influence of chemotherapeutic agents to tumor genetics. This chemical-genetic interaction map can aid in identifying new factors that dictate responses to chemotherapy and prioritize drug combinations.
Scientists developed metaVIPER to assess protein activity in orphan tissues and single cells by integrative analysis of multiple, non-tissue-matched regulatory models. This approach could help to identify critical dependencies within molecularly heterogeneous sub-populations of cancer tissues.
Researchers developed MethylMix 2.0, an algorithm implemented in R that facilitates automated downloading and preprocessing of DNA methylation and gene expression datasets from pan-cancer studies. The tool can be used to identify disease specific hyper and hypomethylated genes and cancer subtyping.