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OPENSEQ.org
AOkdm1a_cam
Genes: A B A+B
Length: 580 148 695
Sequences: 499 6826 129
Seq/Len: 0.86 46.12 0.19
MirrorTree (Pazo et al. 2001) 0.35
Download Alignment
We filter this alignment to remove positions that have > 75% gaps before running GREMLIN.

[Show HHblits results] - Maybe useful in deciding what regions to trim.
Δgene Ratio of paralogs Joined
A B Seq/Len
1 0.01 0.07 0.00
2 0.01 0.07 0.00
5 0.01 0.08 0.01
10 0.01 0.09 0.01
20 0.01 0.09 0.01
100 0.02 0.14 0.05
∞ 0.05 0.18 0.18
Paired alignment generation
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Sequence A E-value:
Iterations:
Sequence B E-value:
Iterations:
Δgene MSA
Figure 1: The effect of Δgene on ratio of paralogs in the genome for each gene, and the number of sequences in the resulting joined alignment. Figure 2: Distribution of Δgene across all genomes. Figure 3: Current parameters. You can use the form to adjust the parameters and resubmit the job!
GREMLIN results (Scaled_score > 1):
Figure 4: The darker and larger the blue dots, the higher strength in coevolution. 		Inter Residue pairs sorted by strength in coevolution signal:
i j Scaled Score Prob I_Prob
321_V 128_A 1.15 0.16 0.00
298_G 93_D 1.11 0.15 0.00
349_V 92_F 1.11 0.15 0.00
9_V 45_E 1.07 0.14 0.00
379_V 72_M 1.04 0.13 0.00
313_K 27_I 1.04 0.13 0.00
49_R 100_I 1.03 0.13 0.00
342_F 27_I 1.03 0.13 0.00
482_D 68_F 0.99 0.12 0.00
349_V 68_F 0.99 0.12 0.00
13_G 93_D 0.99 0.12 0.00
36_E 93_D 0.99 0.12 0.00
42_G 93_D 0.99 0.12 0.00
43_G 93_D 0.99 0.12 0.00
9_V 61_G 0.97 0.11 0.00
321_V 15_A 0.96 0.11 0.00
357_V 61_G 0.95 0.11 0.00
365_V 28_T 0.94 0.11 0.00
365_V 46_A 0.93 0.10 0.00
553_I 92_F 0.91 0.10 0.00
22_A 20_D 0.90 0.10 0.00
399_W 93_D 0.89 0.10 0.00
369_P 68_F 0.89 0.09 0.00
39_D 133_D 0.89 0.09 0.00
12_I 136_V 0.88 0.09 0.00
479_W 93_D 0.88 0.09 0.00
389_K 93_D 0.88 0.09 0.00
321_V 65_F 0.87 0.09 0.00
524_L 34_T 0.86 0.09 0.00
508_I 86_R 0.86 0.09 0.00
Figure 5: The i (protein A) and j (protein B) are positions as given in the query sequences.

Scaled Score = raw_score/average(raw_scores)
Prob = P(contact | scaled_score, seq/len)
I_Prob = P(contact | scaled_score, seq/len, top_inter_score)
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