Corpus ID: 220936378

Two-step penalised logistic regression for multi-omic data with an application to cardiometabolic syndrome

@inproceedings{Cabassi2020TwostepPL,
  title={Two-step penalised logistic regression for multi-omic data with an application to cardiometabolic syndrome},
  author={Alessandra Cabassi and Denis Seyres and M. Frontini and P. Kirk},
  year={2020}
}
  • Alessandra Cabassi, Denis Seyres, +1 author P. Kirk
  • Published 2020
  • Mathematics
  • 1MRC Biostatistics Unit, University of Cambridge, UK 2National Institute for Health Research BioResource, Cambridge University Hospitals, UK 3Department of Haematology, University of Cambridge, UK 4NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK 5Institute of Biomedical & Clinical Science, College of Medicine and Health, University of Exeter Medical School, UK 6British Heart Foundation Centre of Excellence, Cambridge Biomedical Campus, UK 7Cambridge Institute of Therapeutic… CONTINUE READING
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    • 1
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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 31 REFERENCES
    Gene prioritization through genomic data fusion
    • 864
    • PDF
    R: A language and environment for statistical computing.
    • 172,297
    • PDF
    Calculating the sample size required for developing a clinical prediction model
    • 22
    • PDF
    Gaussian Processes for Machine Learning
    • 7,280
    • Highly Influential
    • PDF
    Regularization Paths for Generalized Linear Models via Coordinate Descent.
    • 8,033
    • PDF
    Plasma proteome analysis in HTLV-1-associated myelopathy/tropical spastic paraparesis
    • 15
    • PDF