CTD²: Cancer Target Discovery and Development

CTD2 bridges the gap between the enormous volumes of data generated by genomic characterization studies and the ability to use these data for the development of human cancer therapeutics. It specializes in computational and functional genomics approaches critical for translating next-generation sequencing data, as well as high-throughput and high content small molecule and genetic screens.

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Last updated: January 12, 2018

News & Publications

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Graphical Abstract from McMillan et al., 2018.
CTD²
May 03, 2018

Diversity in the genetic lesions that cause cancer is extreme. In consequence, a pressing challenge is the development of drugs that target patient-specific disease mechanisms. To address this challenge, we employed a chemistry-first discovery paradigm for de novo identification of druggable...

Graphical Abstract from Huang et al., 2018.
CTD²
April 25, 2018

Gene networks are rapidly growing in size and number, raising the question of which networks are most appropriate for particular applications. Here, we evaluate 21 human genome-wide interaction networks for their ability to recover 446 disease gene sets identified through literature curation,...

Applying differential weight as a function of Area Under Curve (AUC)
CTD²
April 24, 2018

Motivation: In recent years there have been several efforts to generate sensitivity profiles of collections of genomically characterized cell lines to panels of candidate therapeutic compounds. These data provide the basis for the development of in silico models of sensitivity...

Graphical Abstract from Hu et al., 2018.
CTD²
April 17, 2018

Chemotherapy is used to treat most cancer patients, yet our understanding of factors that dictate response and resistance to such drugs remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells charting the impact of the...

Heat map of the expression of ABC transporter genes in Tetrahymena
CTD²
April 16, 2018

We and others have shown that transition and maintenance of biological states is controlled by master regulator proteins, which can be inferred by interrogating tissue-specific regulatory models (interactomes) with transcriptional signatures, using the VIPER algorithm. Yet, some tissues may lack...

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