The basic idea of alignment-graph-based method is that false positive protein interactions are rare possible to duplicate in other species and merging two PPI networks being compared according homologous mappings between proteins can filter false positive protein interactions.
Reviewer's report 1: Mr Alexander Panchin, Institute of Information Transmission Problems, Russian Academy of Sciences (nominated by Dr Mikhail Gelfand, Russian Academy of Sciences) The article "Next-generation phylogenomics" by Cheong Xin Chan and Mark A. Ragan addresses the idea of alignment-free methods for phylogenetic analysis using abundant next generation genome-wide data.
The basic idea of alignment-free methods is to use the occurrence or frequency of k-tuples (k-mers, k-grams) as sequence signatures of the studied genomes or metagenomes, and use such signatures as features for the clustering or classification.
Traditionally, the idea of alignment-free methods is to compare two sequences S1 and S2, of length l1 and l2, based on the numbers of occurrences of all words w of length k over the alphabet Σ={ A, C, G, T}.
The alignment-based methods utilize the idea of graph alignment that is conceptually similar to sequence alignment.
Sequence-structure alignment methods can be further divided into 4 kinds by the core idea of the alignment: motif-based methods, pairs-based methods, patch-based methods, and graph-based methods.
The idea of signal alignment was first introduced for MIMO Y channels[9].
The developed implementation scheme is based on the idea of nested alignment and can guarantee the superimposed interference decodable at every receiver with any kind of power relationships.
For MIMO interference channel, the idea of interference alignment (IA) [6] was developed for interference suppression by arranging the desired signal and interference into appropriated signal spaces.
We need to move away from the idea of absolute alignment of interests, THE BIG IDEA.
