Finding sequence motifs with Bayesian models incorporating positional information: an application to transcription factor binding sites

Table 1 The A-GLAM output with positional information for 'hm08r'.

Name	Start	Alignment	End	Score	E-value
seq_0	-66	GTCACGGC	-59	11.0093	6.65E-06
seq_2	-65	GTGACGTT	-58	10.3315	2.30E-05
seq_3	-58	ATGACGTC	-51	11.2688	2.94E-06
seq_5	-188	GTGACGTC	-181	11.4594	1.28E-06
seq_7	-184	CTGACG AC	-177	9.86871	4.64E-05
seq_9	-101	ATGACGTC	-94	10.9283	8.09E-06
seq_10	-220	ATCACGGC	-213	7.58906	3.78E-04
seq_11	-80	GTGACGTC	-73	11.1306	4.75E-06
seq_12	-52	CTGACGGC	-45	10.0764	3.50E-05
seq_14	-8	CTGATGTC	-1	7.60515	3.69E-04

A-GLAM predicted TFBSs in 10 data subsets in the TSS Tompa data subset hm08r'. The column "Name" shows each data subset; the column "Alignment", the corresponding predicted TFBS. The start and end positions with respect to the corresponding TSS are shown in the columns "Start" and "End". The columns "Score" and "E-value" show bit scores and E-values that A-GLAM assigned to predicted TFBSs. The known binding sites in the alignment are underlined.

ISSN: 1471-2105