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- W2611757058 endingPage "609" @default.
- W2611757058 startingPage "599" @default.
- W2611757058 abstract "Introduction: The development of improved cancer therapies is frequently cited as an urgent unmet medical need. Recent advances in platform technologies and the increasing availability of biological ‘big data’ are providing an unparalleled opportunity to systematically identify the key genes and pathways involved in tumorigenesis. The discoveries made using these new technologies may lead to novel therapeutic interventions.Areas covered: The authors discuss the current approaches that use ‘big data’ to identify cancer drivers. These approaches include the analysis of genomic sequencing data, pathway data, multi-platform data, identifying genetic interactions such as synthetic lethality and using cell line data. They review how big data is being used to identify novel drug targets. The authors then provide an overview of the available data repositories and tools being used at the forefront of cancer drug discovery.Expert opinion: Targeted therapies based on the genomic events driving the tumour will eventually inform treatment protocols. However, using a tailored approach to treat all tumour patients may require developing a large repertoire of targeted drugs." @default.
- W2611757058 created "2017-05-12" @default.
- W2611757058 creator A5005499225 @default.
- W2611757058 creator A5033259918 @default.
- W2611757058 creator A5085283148 @default.
- W2611757058 date "2017-05-02" @default.
- W2611757058 modified "2023-09-27" @default.
- W2611757058 title "‘Big data’ approaches for novel anti-cancer drug discovery" @default.
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