Published November 24, 2018 | Version 1.0
Software Open

A machine learning platform to optimize the translation of personalized network models to the clinic

Authors/Creators

  • 1. Centre for Systems Medicine, Department of Physiology & Medical Physics, Royal College of Surgeons in Ireland, Dublin 2, Ireland;
  • 2. OncoMark Ltd., NovaUCD, Belfield Innovation Park, Dublin 4, Ireland;
  • 3. Department of Surgery, Beaumont Hospital, Dublin 9, Ireland;
  • 4. Centre for Systems Medicine, Department of Physiology & Medical Physics, Royal College of Surgeons in Ireland, Dublin 2, Ireland; Department of Pathology, Beaumont Hospital, Dublin 9, Ireland;
  • 5. INSERM UMR-S1147, Personalized Medicine, Pharmacogenomics, Therapeutic Optimization, Université Paris Descartes, Paris, France;
  • 6. Centre for Cancer Research and Cell Biology, School of Medicine, Dentistry and Biomedical Science, Queen's University Belfast, Belfast, United Kingdom;
  • 7. Institute of Cell Biology and Immunology, University of Stuttgart, Germany; Stuttgart Research Center Systems Biology, University of Stuttgart, Germany;

Description

Datasets (clinical and proteomics) and source code for the manuscript "A machine learning platform to optimize the translation of personalized network models to the clinic" in press at  JCO Clinical Cancer Informatics.

Files generated by running the software (as described in the ReadMe), including "outputs" (simulation results, prediction from classification decision trees and statistical results) and resulting f"figures_and_tables" are also provided in "precomputed_files.zip".

Notes

JHMP was also supported by the Irish Cancer Society Collaborative Cancer Research Centre BREAST-PREDICT (CCRC13GAL). The authors wish to acknowledge the DJEI/DES/SFI/HEA Irish Centre for High-End Computing (ICHEC) for the provision of computational facilities and support.

Files

manuela_s-translating_network_biomarkers_into_the_clinic-1cfc46a952f1.zip

Files (651.6 MB)

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Additional details

Related works

Is supplemented by
https://bitbucket.org/manuela_s/translating_network_biomarkers_into_the_clinic/src/v1.0/ (URL)

Funding

Science Foundation Ireland
BCL-2 family proteins and cellular bioenergetics in the control of cell survival: Towards novel predictive and prognostic markers for disease progression and therapy responses in colorectal cancer patients 13/IA/1881
European Commission
APO-DECIDE - Apoptosis Modelling for Treatment Decisions in Colorectal Cancer 306021
Science Foundation Ireland
Development of personalised medicine approaches for the clinical application of IAP antagonists in metastatic and high risk early stage colorectal cancer 14/IA/2582