DNNESCAN has discovered 25 putative TFBSs for 14 TF proteins in 3 genomic regions. See scan settings.

Discovered TFBSs

#Chr	Promoter ID	TF	Strand	Kmer ID	Kmer	Rel. Start	Rel. End	Abs. Start	Abs. End
1	IGR_Upstream_YAL053W	PHD1(motif, model)	+	9	GGGCAA	9	14	45031	45036
1	IGR_Upstream_YAL053W	UME6(motif, model)	+	121	TAGCCGCCCA	121	130	45143	45152
1	IGR_Upstream_YAL053W	SUT1(motif, model)	+	216	GCTCGG	216	221	45238	45243
1	IGR_Upstream_YAL053W	UME6(motif, model)	-	218	TTGCCGCCGA	218	227	45240	45249
1	IGR_Upstream_YAL053W	SUT1(motif, model)	+	308	ACGGCA	308	313	45330	45335
1	IGR_Upstream_YAL053W	FKH1(motif, model)	+	315	GTCAACAG	315	322	45337	45344
1	IGR_Upstream_YAL053W	PHD1(motif, model)	-	327	AGGCAC	327	332	45349	45354
1	IGR_Upstream_YAL053W	SUT1(motif, model)	-	358	CCGGAT	358	363	45380	45385
1	IGR_Upstream_YAL053W	FHL1(motif, model)	-	447	ATGTACGGCT	447	456	45469	45478
1	IGR_Upstream_YAL053W	CBF1(motif, model)	-	458	GGCACGTG	458	465	45480	45487
1	IGR_Upstream_YAL053W	ABF1(motif, model)	+	478	ATCATTCTGGACG	478	490	45500	45512
1	IGR_Upstream_YAL053W	REB1(motif, model)	-	530	TTACCCGA	530	537	45552	45559
1	IGR_Upstream_YAL053W	SWI5(motif, model)	+	604	TGCTGT	604	609	45626	45631
1	IGR_Upstream_YAL053W	DIG1(motif, model)	-	608	AGAAAC	608	613	45630	45635
1	IGR_Upstream_YAL053W	SWI4(motif, model)	-	626	CGCGAAA	626	632	45648	45654
1	IGR_Upstream_YAL053W	SUT1(motif, model)	+	630	GCGCGA	630	635	45652	45657
1	IGR_Upstream_YAL053W	SWI5(motif, model)	-	640	GGCTGA	640	645	45662	45667
2	IGR_Upstream_YBR146W	ABF1(motif, model)	-	266	ATCATTTTATACG	266	278	535083	535095
14	IGR_Upstream_YNL118C	ABF1(motif, model)	-	174	ATCACTAAGCACG	174	186	405738	405750
14	IGR_Upstream_YNL118C	REB1(motif, model)	-	202	TTACCCTG	202	209	405766	405773
14	IGR_Upstream_YNL118C	ABF1(motif, model)	+	225	ATCACTATATACG	225	237	405789	405801
14	IGR_Upstream_YNL118C	SUT1(motif, model)	-	343	GCCGGG	343	348	405907	405912
14	IGR_Upstream_YNL118C	SWI5(motif, model)	-	352	TGCCGG	352	357	405916	405921
14	IGR_Upstream_YNL118C	SKN7(motif, model)	-	362	CCTCGGCC	362	369	405926	405933
14	IGR_Upstream_YNL118C	SUT1(motif, model)	+	363	GCCGAG	363	368	405927	405932

TF Motifs

ABF1	CBF1	DIG1	FHL1
FKH1	PHD1	REB1	SKN7
SOK2	STE12	SUT1	SWI4
SWI5	UME6

DNNESCAN Models

ABF1: Selected features [PWMConst, Twist_shift(CC/GG)], DNNE model [2 inputs, 1 output(s), 5 RVFLNs, 5 neurons, lambda=0.55], AEF Model [lambda1=0.00005, lambda2=0.01654]
CBF1: Selected features [PWMConst, PhylCons], DNNE model [2 inputs, 1 output(s), 5 RVFLNs, 10 neurons, lambda=0.55], AEF Model [lambda1=0.00004, lambda2=0.10526]
DIG1: Selected features [PWMConst, PhylCons, Slide stiffness(TA/AT)], DNNE model [3 inputs, 1 output(s), 5 RVFLNs, 10 neurons, lambda=0.55], AEF Model [lambda1=0.00044, lambda2=0.20234]
FHL1: Selected features [PWMConst, Tip(AC/TG)], DNNE model [2 inputs, 1 output(s), 5 RVFLNs, 10 neurons, lambda=0.55], AEF Model [lambda1=0.00100, lambda2=0.06840]
FKH1: Selected features [DNA-BAS(Width), PhylCons], DNNE model [2 inputs, 1 output(s), 5 RVFLNs, 10 neurons, lambda=0.55], AEF Model [lambda1=0.00022, lambda2=0.12405]
PHD1: Selected features [PWMConst, PhylCons], DNNE model [2 inputs, 1 output(s), 5 RVFLNs, 10 neurons, lambda=0.55], AEF Model [lambda1=0.00059, lambda2=0.08171]
REB1: Selected features [PWMConst, Clash Strength(CG/GC), Guanine content, Slide stiffness(CC/GG), Clash Strength(GC/CG)], DNNE model [5 inputs, 1 output(s), 5 RVFLNs, 10 neurons, lambda=0.55], AEF Model [lambda1=0.00009, lambda2=0.07627]
SKN7: Selected features [PWMConst, PhylCons, RevComp], DNNE model [3 inputs, 1 output(s), 5 RVFLNs, 10 neurons, lambda=0.55], AEF Model [lambda1=0.00162, lambda2=0.07291]
SOK2: Selected features [PWMConst, PhylCons, Tip(CA/GT)], DNNE model [3 inputs, 1 output(s), 5 RVFLNs, 10 neurons, lambda=0.55], AEF Model [lambda1=0.00137, lambda2=0.06748]
STE12: Selected features [PWMConst, PhylCons, Flexibility_slide(AT/TA), Major Groove Distance(GC/CG), Stacking energy(MEAN)], DNNE model [5 inputs, 1 output(s), 5 RVFLNs, 5 neurons, lambda=0.55], AEF Model [lambda1=0.00019, lambda2=0.10231]
SUT1: Selected features [ConsSym, PhylCons, Clash Strength(AC/TG)], DNNE model [3 inputs, 1 output(s), 5 RVFLNs, 10 neurons, lambda=0.55], AEF Model [lambda1=0.00142, lambda2=0.08346]
SWI4: Selected features [PWMConst, PhylCons, Major Groove Distance(GC/CG), Tilt_rise(GA/CT)], DNNE model [4 inputs, 1 output(s), 5 RVFLNs, 10 neurons, lambda=0.55], AEF Model [lambda1=0.00035, lambda2=0.18382]
SWI5: Selected features [PWMConst, PhylCons, Major Groove Distance(GC/CG), Twist_shift(AA/TT)], DNNE model [4 inputs, 1 output(s), 5 RVFLNs, 5 neurons, lambda=0.55], AEF Model [lambda1=0.00137, lambda2=0.12678]
UME6: Selected features [PWMConst, PhylCons], DNNE model [2 inputs, 1 output(s), 5 RVFLNs, 5 neurons, lambda=0.55], AEF Model [lambda1=0.00016, lambda2=0.04463]

DNNESCAN Settings

Operation: scan
TF protein(s): all
Input file format: genes
Output format: html
Overlapping removal: all