Table 2.

Gene network inference methods

Method	Algorithm type	Bulk or single cell	Directed or undirected	Citation	Code source
Pearson Correlation	correlation	both	undirected	Stuart et al., 2003	various
PIDC	partial information decomposition	both	undirected	Chan et al., 2017	https://github.com/Tchanders/ NetworkInference.jl
ARACNE	mutual information	both	undirected	Margolin et al., 2006	https://github.com/califano- lab/GPU-ARACNE
GENIE3	decision tree ensembles	both	directed	Huynh-Thu et al., 2010	https://arboreto.readthedocs. io/en/latest/index.html
SCODE	ordinary differential equations	single cell	directed	Matsumoto et al., 2017	https://github.com/hmatsu1226/SCODE
SINCERITIES	Granger causality	single cell	directed	Papili Gao et al., 2018	https://github.com/CABSEL/SINCERITIES
SINGE	Granger causality	single cell	directed	Deshpande et al., 2019	https://github.com/gitter-lab/SINGE
Scribe	directed information	single cell	directed	Qiu et al., 2020	https://github.com/cole-trapnell-lab/Scribe
scTenifoldKnk	principal components regression and tensor decomposition	single cell	directed	Osorio et al., 2021	https://github.com/cailab- tamu/scTenifoldKnk
CellBox	ordinary differential equations	bulk proteomics	directed	Yuan et al., 2021	https://github.com/sanderlab/CellBox

Table containing methods described in this review for or involving gene/protein network inference. These methods use transcriptomics data as input unless otherwise indicated.