citation.bib

@ARTICLE{Vogelstein2019mgc,
  title    = "Discovering and deciphering relationships across disparate data
              modalities",
  author   = "Vogelstein, Joshua T and Bridgeford, Eric W and Wang, Qing and
              Priebe, Carey E and Maggioni, Mauro and Shen, Cencheng",
  abstract = "Understanding the relationships between different properties of
              data, such as whether a genome or connectome has information
              about disease status, is increasingly important. While existing
              approaches can test whether two properties are related, they may
              require unfeasibly large sample sizes and often are not
              interpretable. Our approach, 'Multiscale Graph Correlation'
              (MGC), is a dependence test that juxtaposes disparate data
              science techniques, including k-nearest neighbors, kernel
              methods, and multiscale analysis. Other methods may require
              double or triple the number of samples to achieve the same
              statistical power as MGC in a benchmark suite including
              high-dimensional and nonlinear relationships, with dimensionality
              ranging from 1 to 1000. Moreover, MGC uniquely characterizes the
              latent geometry underlying the relationship, while maintaining
              computational efficiency. In real data, including brain imaging
              and cancer genetics, MGC detects the presence of a dependency and
              provides guidance for the next experiments to conduct.",
  journal  = "Elife",
  volume   =  8,
  month    =  jan,
  year     =  2019,
  keywords = "computational biology; data science; human; machine learning;
              neuroscience; statistics; systems biology",
  language = "en"
}

@techreport{Bridgeford2018_mgcpkg,
    author = {Bridgeford, Eric W and Shen, Censheng and Wang, Shangsi and Vogelstein, Joshua},
    doi = {10.5281/ZENODO.1246967},
    month = {may},
    title = {{Multiscale Graph Correlation}},
    url = {https://zenodo.org/record/1246967},
    year = {2018}
}