The phrase "alignment to classify" is correct and usable in written English.
It can be used in contexts related to data analysis, machine learning, or categorization tasks where alignment is necessary for classification purposes.
Example: "The algorithm requires proper alignment to classify the data accurately into the specified categories."
Alternatives: "alignment for categorization" or "alignment for classification purposes".
The method exploits information from the reference alignments to classify the sequences in each alignment into a number of subfamilies and to construct a representative model for each protein subfamily, including characteristic conserved blocks and typical start/stop sites.
Mano et al. (2010) considered the topology of pathways as chains and used a pathway alignment method to classify species.
Phylogenetic analysis of an RT nucleotide sequence alignment was used to classify the chicken ERV sequences that we identified.
These protein sequence alignments were used to classify all the residues in each RNA binding protein into 9 categories: highly variable (score: 1) to highly conserved (score: 9).
Since a threshold of alignments is required to classify a sequence as Y-linked, higher coverage male and female sequence data leads to the identification of more Y-sequences.
In cases where both mate-pair reads from a single BAC could each be mapped to a discrete location in the mouse genome, the orientation and distance between the mate-pair alignments was used to classify clones as 'concordant' (orientation: + and - strand; distance: 90-200 kb) or 'discordant' (orientation: + and + strand, or - and - strand; distance: < 90 kb or > 200 kb).
In cases where both of the mate-pair reads from a single BAC mapped to one location in the zebra finch genome, the orientation and distance between the mate-pair alignments were used to classify clones as "concordant" (orientation: + and – strand; distance: 90 200 kb) or "discordant" (orientation: + and + strand or – and – strand; distance: <90 kb or >200 kb).
The alignment also helped us to classify the SLBB superfamily into several distinct families.
This is the first study to use whole genome alignment and phylogenetic methods to classify A. baumannii.
In addition to the original start position (i.e. the position from which a read is simulated) that was used in most previous studies, the end position as well as the numbers of insertions, deletions, and substitutions in the alignment were also used to classify the mapping of a read as correct.
