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Transcription_factors, a subtype of Protein, connect to Genes via regulation relations.
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A high confidence regulation relation is denoted by a bold line.
The proposed gene expression relation mining system, AutoPat, applied the weighted patterns to extract regulation relation information from literature.
The RCS is a measurement for the confidence of the curated TFKO TF-gene regulation relation or the deduced hypostatic TF-gene regulation relation as described in the Methods section.
A regulation relation with RCS higher than 1000 was set to be confident.
And the knockout effect of this hypostatic regulation relation may thereby be masked.
Therefore, we constructed a regulatory relation network from the TFKO data and sought the hypostatic TF-gene regulation relation by checking the existence of a regulation path in the regulation relation network for the given ChIP postives.
The literature-curated TFKO regulation relation and the deduced hypostatic regulation regulation for given ChIP positive TF-gene binding pairs were also checked through regulatory confidence scores (RCS).
Since there are inherent uncertainties in the high-throughput technologies, the TFKO regulation relation or the deduced hypostatic TF-gene cascade regulation may be introduced by chance.
Hence we further considered the possible hypostatically masked (to the epistatic regulation cascade) TF-gene regulation relation deduced from the original TFKO data.
Because of this reason, as a second step, the curated TFKO regulation relation or the deduced hypostatic regulation relation for the given TF-gene ChIP positive was also checked by the regulatory confidence score (RCS), which was scored through the comparison with random TFKO data (See Methods section).
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