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Figure 6 | BMC Bioinformatics

Figure 6

From: Reconstructing genome-wide regulatory network of E. coli using transcriptome data and predicted transcription factor activities

Figure 6

GTRNetwork algorithm combinations on input initial network of 90% RegulonDB 7.0 data. 10% of links are randomly deleted. Five runs were made for each recall level. The trend lines of data points are fitted by polynomial functions. Under this condition the combination E-A-C (EM-based TFA prediction, APMI relevance score with CLR background correction) and E-A-N (EM-based TFA prediction, APMI relevance score without CLR background correction) give the best performances. All the TFA based algorithms show significantly better performance than the algorithms not using TFA information.

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