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Table 1 Empirical biological knowledge estimation

From: Using empirical biological knowledge to infer regulatory networks from multi-omics data

Edge

Operation

Frequency

Candidate

Acceptance

\(G_i\) \(G_j\)

Add

\(f_{ij} = f_{ij} + 1\)

Accepted

\(a_{ij} = a_{ij} + 1\)

Rejected

\(a_{ij} = a_{ij}\)

\(G_i\) \(G_j\)

Delete

\(f_{ij} = f_{ij} + 1\)

Accepted

\(a_{ij} = a_{ij}\)

Rejected

\(a_{ij} = a_{ij} + 1\)

\(G_i\) \(G_j\)

Reverse

\(f_{ij} = f_{ij} + 1\)

Accepted

\(a_{ij} = a_{ij}\)

\(a_{ji} = a_{ji} + 1\)

\(f_{ji} = f_{ji} + 1\)

Rejected

\(a_{ij} = a_{ij} + 1\)

\(a_{ji} = a_{ji}\)

  1. Assuming there is no prior knowledge about the direct interaction from node i to node j, the empirical biological matrix \({\mathcal {B}}\) is estimated, with \({\mathcal {B}}_{ij} = \frac{a_{ij}}{f_{ij}} \in [0,1]\)