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Background Given expression data, gene regulatory network(GRN) inference approaches try to determine regulatory relations. However, current inference methods ignore the inherent topological characters of GRN to some extent, leading to structures that lack clear biological explanation. To increase the biophysical meanings of inferred networks, this study performed data-driven module detection before network inference. Gene modules were identified by decomposition-based methods. Resultsdoi:10.1186/s12859-021-04074-y pmid:33761871 fatcat:5nfj4uyh5zagpfgzrkps6wgqqu