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OPENSEQ.org
Elodie
Genes: A B A+B
Length: 237 122 351
Sequences: 84286 89235 34199
Seq/Len: 355.64 731.43 97.43
MirrorTree (Pazo et al. 2001) 1.09
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 0.04 0.11 77.68
2 0.07 0.13 82.60
5 0.11 0.16 86.67
10 0.14 0.19 90.78
20 0.18 0.23 95.26
100 0.28 0.31 105.87
∞ 0.32 0.34 108.42
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
27_A 17_I 1.91 1.00 0.98
54_Q 13_V 1.69 1.00 0.96
23_T 14_L 1.65 1.00 0.95
46_E 16_K 1.49 1.00 0.92
50_V 16_K 1.47 1.00 0.91
53_D 13_V 1.43 1.00 0.90
47_F 20_F 1.42 0.99 0.89
50_V 13_V 1.28 0.99 0.83
35_S 24_K 1.13 0.97 0.71
30_E 108_S 1.12 0.97 0.70
30_E 109_P 1.11 0.96 0.69
24_A 13_V 1.05 0.94 0.63
31_T 21_N 1.02 0.93 0.60
34_N 24_K 0.99 0.92 0.56
28_Y 17_I 0.94 0.89 0.50
34_N 110_S 0.90 0.86 0.45
43_T 20_F 0.87 0.83 0.41
56_N 108_S 0.85 0.81 0.39
24_A 11_S 0.83 0.79 0.36
43_T 23_K 0.82 0.78 0.35
24_A 14_L 0.72 0.64 0.24
31_T 20_F 0.71 0.63 0.23
57_H 11_S 0.71 0.62 0.22
28_Y 16_K 0.66 0.54 0.18
30_E 110_S 0.65 0.51 0.17
34_N 109_P 0.63 0.48 0.15
26_K 108_S 0.59 0.42 0.13
24_A 17_I 0.56 0.37 0.10
34_N 25_E 0.54 0.34 0.10
23_T 107_F 0.53 0.32 0.09
31_T 17_I 0.52 0.31 0.08
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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