Functional analysis of microRNA and transcription factor synergistic regulatory network based on identifying regulatory motifs in non-small cell lung cancer

Table 4 Details of motifs in the lung cancer synergistic regulatory network

Motif	Z-value^a/P-value^b	Mean^c	Std^c	No. of motifs	No. of genes	No. of TFs	No. of miRNA
I	4.9847/ 0	27.0475	11.8268	86	28	3	12
II	6.9558/ 0	1417.3280	81.6113	1985	180	22	219
III	2.4034/ 0.0097	438.9193	30.8235	513	176	35	66
IV	4.2270/ 0.0001	771.7246	260.5343	1873	520	4	13
V	2.3031/ 0.0162	230.3356	87.9953	433	97	4	13
VI	19.9562/ 0	32689.19	290.5763	38488	422	163	250
VII	27.6201/ 0	114787.3	1225.9080	148647	928	26	243
VIII	2.9824/ 0.0004	19895.26	369.7436	20995	882	56	88
IX	8.3071/ 0	12070.81	267.1441	14290	237	27	242
X	1.2440/ 0.108	4284.108	155.8588	4478	414	56	88

^aZ-value was calculated using the formula (2.4.1).
^bP-value is the proportion of the 10000 random simulations in which a motif had a larger frequency in the random repeats than real in the data.
^cMean and Std are the average and the standard deviation of motif frequency of the 10000 random repeats.
Motif I: Full regulation; II: TF-leading synergistic regulation; III: miRNA leading synergistic regulation; IV: miRNA feedback synergistic regulation; V: TF feedback synergistic regulation; VI: synergistic co-regulation; VII: miRNA simultaneous regulation; VIII: linear regulation from TF; IX: linear regulation from miRNA; and X: TF simultaneous regulation.

ISSN: 1752-0509