rMKL-LPP specifications


Unique identifier OMICS_19214
Alternative name Regularized Multiple Kernel Learning Locality Preserving Projections
Software type Application/Script
Interface Command line interface
Restrictions to use None
Computer skills Advanced
Stability Stable
Maintained Yes


No version available


  • person_outline Nora Speicher
  • person_outline Nico Pfeifer

Publication for Regularized Multiple Kernel Learning Locality Preserving Projections

rMKL-LPP citation


More Is Better: Recent Progress in Multi Omics Data Integration Methods

Front Genet
PMCID: 5472696
PMID: 28670325
DOI: 10.3389/fgene.2017.00084

[…] jections (LPP) is applied to conserve the sum of distances for each sample's k-Nearest Neighbors. The finalized clustering is done through applying k-means on the distance summation. Compared to SNF, rMKL-LPP claims to offer comparable results with much more flexibility, as it provides different choices of dimension reduction methods and a variety of kernels per data type. […]

rMKL-LPP institution(s)
Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbrucken, Germany; Saarbrucken Graduate School of Computer Science, Saarland University, Saarbrucken, Germany

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