From: GNE: a deep learning framework for gene network inference by aggregating biological information
Symbol | Definitions |
---|---|
M | Total number of genes in gene network |
E | Number of expression values for each gene |
N _{ i} | Set of the neighbor genes of gene v_{i} |
\(\textbf {v}_{i}^{(s)}\) | Topological representation of gene v_{i} |
\(\textbf {v}_{i}^{(a)}\) | Attribute representation of gene v_{i} |
\(\widetilde {\textbf {v}}_{i}\) | Neighborhood representation of gene v_{i} |
v _{ i} | Concatenated representation of topological properties and expression data |
k | Number of hidden layers to transform concatenated representation into embedding space |
h ^{( k)} | Output of k^{th} hidden layer |
W _{ k} | Weight matrix for k^{th} hidden layer |
W _{ id} | Weight matrix for topological structure embedding |
W _{ att} | Weight matrix for attribute embedding |
W _{ out} | Weight matrix for output layer |