Algorithm-1: Seeds-Generation on the basis of biological scoring matrices

1: Procedure: Seed Generation 2: Input: M1, M2, and M3 //Similarity Matrices 3: Input: str.t, seq.t and lseq.t //Similarity Thresholds 4: Output: Top-Nodes and Seeds 5: Seeds = [] 6: Sort M1, M2, M3 on the basis of scores 7: for all node pairs (a, b) do 8:  if a ∉ Seeds and b ∉ Seeds and M1[a, b] ⩾ 0.8 then 9:   Seeds.append(a, b) 10:  end if 11: end for 12: for all node pairs (a, b) do 13:  if a ∉ Seeds and b ∉ Seeds and M2[a, b] ⩾ 200 then 14:   Seeds.append(a, b) 15:  end if 16: end for 17: for all node pairs (a, b) do 18:  if a ∉ Seeds and b ∉ Seeds and M3[a, b] ⩾ 4.0 then 19:   if AlignmentLength(a, b) > 35 then 20:    Seeds.append(a, b) 21:   end if 22:  end if 23: end for 24: Top-Nodes = Seeds //Top-Nodes are separated 25: for all node pairs (a, b) do 26:  if a ∉ Seeds and b ∉ Seeds and M1[a, b] ⩾ str.t then 27:   Seeds.append(a, b) 28:  end if 29: end for 30: for all node pairs (a, b) do 31:  if a ∉ Seeds and b ∉ Seeds and M2[a, b] ⩾ seq.t then 32:   Seeds.append(a, b) 33:  end if 34: end for 35: for all node pairs (a, b) do 36:  if a ∉ Seeds and b ∉ Seeds and M3[a, b] ⩾ lseq.t then 37:   if AlignmentLength(a, b) > 35 then 38:    Seeds.append(a, b) 39:   end if 40:  end if 41: end for 42: end procedure