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  • PDX Finder is an open repository for the upload and storage of clinical, genomic and functional Patient-Derived Xenograph (PDX) data which provides a comprehensive global catalogue of PDX models available for researchers across distributed repository databases. Integrated views are provided for histopathological image data, molecular classification of tumors, host mouse strain metadata, tumor genomic data and metrics on tumor response to chemotherapeutics. The data model for PDX Finder is based on the minimal information standard for PDX models developed in collaboration with a broad range of stakeholders who create and/or use PDX models in basic and pre-clinical cancer research.

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  • This site is an institutional repository providing access to the research output of the institution. Many items are not available as full-text. Users may set up RSS and Atom feeds to be alerted to new content.

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  • This site is a subject based repository for all areas of cognitive science, including related areas of philosophy, biology and mathematics. While the principle language of the materials deposited on this site is English, there are a few articles available in other languages. Users may set up RSS and Atom feeds to be alerted to new content.

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  • Nearly 60% of patients undergoing cancer treatment are estimated to have had at least one potential drug-drug interaction; for patients receiving oral anticancer therapy, up to 50% have been reported to experience a potential drug-drug interaction, with 16% experiencing a major event. Drug-drug interactions are therefore a significant issue for cancer patients and the health care professionals who treat them. Combining the internationally recognised drug-drug interactions expertise of the University of Liverpool (UK) with the clinical pharmacology in oncology and haemotology expertise of Radboud University, Nijmegen (the Netherlands), this site was established in 2017 in response to the need for improved management of DDIs with anti-cancer agents.

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5,195 Data sources
  • more_vert
  • PDX Finder is an open repository for the upload and storage of clinical, genomic and functional Patient-Derived Xenograph (PDX) data which provides a comprehensive global catalogue of PDX models available for researchers across distributed repository databases. Integrated views are provided for histopathological image data, molecular classification of tumors, host mouse strain metadata, tumor genomic data and metrics on tumor response to chemotherapeutics. The data model for PDX Finder is based on the minimal information standard for PDX models developed in collaboration with a broad range of stakeholders who create and/or use PDX models in basic and pre-clinical cancer research.

    more_vert
  • This site is an institutional repository providing access to the research output of the institution. Many items are not available as full-text. Users may set up RSS and Atom feeds to be alerted to new content.

    more_vert
  • more_vert
  • more_vert
  • more_vert
  • This site is a subject based repository for all areas of cognitive science, including related areas of philosophy, biology and mathematics. While the principle language of the materials deposited on this site is English, there are a few articles available in other languages. Users may set up RSS and Atom feeds to be alerted to new content.

    more_vert
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  • Nearly 60% of patients undergoing cancer treatment are estimated to have had at least one potential drug-drug interaction; for patients receiving oral anticancer therapy, up to 50% have been reported to experience a potential drug-drug interaction, with 16% experiencing a major event. Drug-drug interactions are therefore a significant issue for cancer patients and the health care professionals who treat them. Combining the internationally recognised drug-drug interactions expertise of the University of Liverpool (UK) with the clinical pharmacology in oncology and haemotology expertise of Radboud University, Nijmegen (the Netherlands), this site was established in 2017 in response to the need for improved management of DDIs with anti-cancer agents.

    more_vert
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