Oct 29, 2018 · Here, we propose an efficient method, named ConMod, to discover conserved functional modules in multiple biological networks.
Results Here, we propose an efficient method, named ConMod, to discover conserved functional modules in multiple biological networks. We introduce two features ...
This algorithm is used for identifying conserved functional modules in multiple networks, as described in: Feature related multi-view nonnegative matrix ...
Feature related multi-view nonnegative matrix factorization for identifying conserved functional modules in multiple biological networks. P Wang, L Gao, Y Hu ...
Application of non-negative matrix factorization in oncology - NCBI
www.ncbi.nlm.nih.gov › PMC9294421
Jul 5, 2022 · Non-negative matrix factorization (NMF) is a machine learning technique used for image analysis, speech recognition, and language processing.
Specifically, LSCC jointly factorizes multi-layer networks by projecting all layers into a common subspace with nonnegative matrix factorization, where the ...
Feature related multi-view nonnegative matrix factorization for identifying conserved functional modules in multiple biological networks. BMC Bioinformatics ...
Apr 21, 2020 · Feature related multi-view nonnegative matrix factorization for identifying conserved functional modules in multiple biological networks.
Dec 18, 2013 · In this paper, we propose a novel NMF-based multi-view clustering algorithm by searching for a factorization that gives compatible clustering solutions across ...
The ConMod includes three main steps: 1. transform multiple networks into two feature matrices, 2. factorize the two feature matrices jointly using multiview�...