The basic idea of network consistency is that, if miRNAs are ranked by their relevance to a query miRNA, and phenotypes are ranked by their relevance to the hidden target phenotype of the query miRNA, the top-ranked miRNAs and the top-ranked disease phenotypes should be highly connected by known associations.
The algorithm performs a dynamic local alignment between the query miRNA sequence and the reference sequence where G U wobble is allowed and generates scores for the alignments found.
To make full use of global network similarity information, we compute the global relevance score between the query miRNA m and all the miRNAs based on the graph Laplacian of the miRNA functional similarity network M(n*n).
Plant sp, NSs, Nucleotide substitutions between known plant query miRNAs and the corresponding miRNA in Boechera sexual species; NN, Number of nucleotides hairpin length; ARM, mature miRNA location in hairpin structure; AMFE, Adjusted minimum fold energy; MFEI, Minimum fold energy index; EST ID, Identifier of the 454 transcripts from which miRNA was derived.
Plant sp, NSs, Nucleotide substitutions between known plant query miRNAs and the corresponding miRNA in Boechera apomictic species; NN, Number of nucleotides hairpin length; ARM, mature miRNA location in hairpin structure; AMFE, Adjusted minimum fold energy; MFEI, Minimum fold energy index; EST ID, Identifier of the 454 transcripts from which miRNA was derived.
Our method uses consistency in networks to measure whether the query miRNA m and a target phenotype p show coherent association with the known miRNA-phenotype associations.
We simply go through each phenotype and compute a Pearson correlation coefficient score against the query miRNA m for each case.
The query miRNA data set was mapped separately to the A-genome [ 14] and the draft PKW B-genome developed here.
The query miRNA is represented by a binary vector m = [ m1, m2, …, m n ] T denoting the miRNA membership against the miRNA set, i.e. each m i =1 if miRNA i is the query miRNA, otherwise m i =0.
