Published May 24, 2017 | Version v1.0.0
Software Open

Non-negative matrix factorization for subgraph analysis of dynamic networks

Creators

  • 1. University of Pennsylvania

Description

Python toolbox for decomposing dynamical graph models into subgraphs and accompanying time-varying expression weights using non-negative matrix factorization (NMF).

Implementation was derived from https://github.com/kimjingu/nonnegfac-python (Jingu Kim)

Notes

This work was supported by the following funding sources: NIH 1R01HD086888-01, NSF BCS-1631550, NSF BCS-1441502, ONR Young Investigator Program

Files

akhambhati/nonnegfac-v1.0.0.zip

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Additional details

Related works

Cites
10.1101/097691 (DOI)
Is cited by
10.1101/124016 (DOI)
Is supplement to
https://github.com/akhambhati/nonnegfac/tree/v1.0.0 (URL)

References

  • Jingu Kim, Yunlong He, and Haesun Park. Algorithms for Nonnegative Matrix and Tensor Factorizations: A Unified View Based on Block Coordinate Descent Framework. Journal of Global Optimization, 58(2), pp. 285-319, 2014
  • Jingu Kim and Haesun Park. Fast Nonnegative Matrix Factorization: An Active-set-like Method And Comparisons. SIAM Journal on Scientific Computing (SISC), 33(6), pp. 3261-3281, 2011.