Inferring the role of transcription factors in regulatory networks

BMC Bioinformatics

Table 3 Results of the sign inference process on S. cerevisiae

Interaction network	Nodes	Edges	Average observed nodes	In/Out observed simultan.	Inferred signs {+, -}	MBM Type I	MBM Type II-IV	Total Inference	Naive Algorithm Inference
(A) Core of Transc. Network [11,28]	31	52	28%	88%	11	3	0	26.8%	11%
(B) Extended Transc. Network [11]	70	96	26%	72%	29	7	0	37.4%	15,6%
(C) MacIsaac inferred network [12,13]	83	131	33%	69%	21	4	0	19%	11%
(D) Global Transc. Network [11]	2419	4344	30%	52%	no filter : 631 filter k = 3 : 198	281	463	32%	13.9%

Sign inference process applied on four transcriptional networks of S. cerevisiae. 15 significant (2-fold) experiments were used for the inference. The In/Out observed simultaneously rate refers to the possible sign inference rate if all observations of the in/out nodes of one edge lead to predictions. The Inferred signs are the number of signs fixed in an unique way {+, -} by all the experiments; MBM Type I, refers to the number of edges found in a module of this type; and analogusly for MBM Type II-IV. The sum of these 3 values divided by the total number of edges will represent the rate of the Total Inference. In addition, we calculated the inference rate obtained with the Naive Algorithm. For network (D) all the inference rates were obtained using the algorithm without filtering, except for the number of Inferred signs.

ISSN: 1471-2105