TY - GEN
T1 - A procedure for identifying master regulators in conjunction with network screening and inference
AU - Saito, Shigeru
AU - Zhou, Xinrong
AU - Bae, Taejeong
AU - Kim, Sunghoon
AU - Horimoto, Katsuhisa
PY - 2010
Y1 - 2010
N2 - We developed a procedure for indentifying transcriptional master regulators (MRs) related to special biological phenomena, such as diseases, in conjunction with network screening and inference. Network screening is a system for detecting activated transcriptional regulatory networks under particular conditions, based on the estimation of the graph structure consistency with the measured data. Since the network screening utilizes the known transcriptional factor (TF)-gene relationships as the experimental evidence for the molecular relationships, its performance depends on the ensemble of known TF networks used for its analysis. To compensate for its restrictions, a network inference method, the path consistency algorithm, is concomitantly utilized to identify MRs. The performance is illustrated by means of the known MRs in brain tumors that were computationally inferred and experimentally verified. As a result, the present procedure worked well for identifying MRs, in comparison to the previous computational selection for experimental verification.
AB - We developed a procedure for indentifying transcriptional master regulators (MRs) related to special biological phenomena, such as diseases, in conjunction with network screening and inference. Network screening is a system for detecting activated transcriptional regulatory networks under particular conditions, based on the estimation of the graph structure consistency with the measured data. Since the network screening utilizes the known transcriptional factor (TF)-gene relationships as the experimental evidence for the molecular relationships, its performance depends on the ensemble of known TF networks used for its analysis. To compensate for its restrictions, a network inference method, the path consistency algorithm, is concomitantly utilized to identify MRs. The performance is illustrated by means of the known MRs in brain tumors that were computationally inferred and experimentally verified. As a result, the present procedure worked well for identifying MRs, in comparison to the previous computational selection for experimental verification.
UR - http://www.scopus.com/inward/record.url?scp=79952430496&partnerID=8YFLogxK
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U2 - 10.1109/BIBM.2010.5706580
DO - 10.1109/BIBM.2010.5706580
M3 - Conference contribution
AN - SCOPUS:79952430496
SN - 9781424483075
T3 - Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010
SP - 296
EP - 301
BT - Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010
T2 - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010
Y2 - 18 December 2010 through 21 December 2010
ER -