Repository containing R code for ontology, pathway and kinase substrate enrichment analysis (with examples) used in this study:
Drug ranking using machine learning (DRUML) systematically predicts the efficacy of anti-cancer drugs
Henry Gerdes 1, Pedro Casado 1, Arran Dokal 1, Maruan Hijazi 1, #, Nosheen Akhtar1, 3, Ruth Osuntola 4, Vinothini Rajeeve 4, Jude Fitzgibbon 5, Jon Travers 6, David Britton 1,2, Shirin Khorsandi 7 & Pedro R. Cutillas 1,4,8*
1 Cell Signalling & Proteomics Group, Centre for Genomics & Computational Biology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, United Kingdom 2 Current address: Kinomica Ltd, Alderley Park, Alderley Edge, Macclesfield SK10 4TG, United Kingdom 3 Department of Biological Sciences, National University of Medical Sciences, Rawalpindi, Pakistan 4 Mass spectrometry Laboratory, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, United Kingdom 5 Personalised Medicine Group, Centre for Genomics & Computational Biology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, United Kingdom 6 Astra Zeneca Ltd, 1 Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge, CB2 0AA, United Kingdom 7 Kings College London, Denmark Hill, Brixton, London SE5 9RS, United Kingdom 8 The Alan Turing Institute, The British Library, 2QR, 96 Euston Rd, London NW1 2DB, United Kingdom
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