The phrase "between any two sequences" is grammatically correct and can be used in written English.
It is often used to describe a relationship or comparison between two sequences of events, objects, or numbers. Example: The researcher found a strong correlation between any two sequences of numbers in the data set.
The maximal level of nucleotide divergence among alleles ranged from 0.37% (gapA) to 1.74% (phoE), while the diversity index π (the average number of nucleotide differences per site between any two sequences chosen randomly from the study sample) ranged from 0.14% (for gapA) to 1.0% (for tonB) (Table 1).
We have studied the effect of different levels of sequence redundancy in the MSA, by calculating MI not only with the original data set of 348 sequences but also with a series of progressively smaller MSAs in which the highest level of identity between any two sequences was 98, 96, 94, 92, 90, 88, 86, 84, 82, 80%.
Finally, the similarity calculation module computes the similarity between any two sequences using their vectors obtained above.
The median distance between any two sequences, based on their soybean orthologous location, was 11,068 nucleotides.
Therefore, variation between any two sequences with a p value less than 0.01 was predicted to be the result of allelic variation or sequence error.
The assumption underlying this software is that the phylogenetic relationship between any two sequences and their degree of similarity are positively correlated.
The AI method also does not take branch lengths into account, and like the SM, is dependent on the structure of the tree, but adds a degree of complexity by weighting the contributions of the nodes between any given two sequences based on where they are located in the tree (i.e. how deep in the tree they are).
Dynamic programming algorithms are widely used to find the optimal sequence alignment between any two DNA sequences.
Similar peptide sequences were clustered by creating a link between any two peptide sequences having an identity above 30% over an amino acid span of at least 50 aa.
By applying a recently described sequence motif-based clustering methodology using thresholds of 50% amino-acid identity and 70% similarity between any two CDR3 sequences, 13 out of 14 CD4+ T-LGL displayed a highly homogeneous and similar TCR with clear similarities in length and amino-acid positions in the CDR3 sequence logo.
In addition, an extended lower bound function is designed to obtain good tightness and fast measure the distance between any two center sequences.
