The phrase "a robust alignment of" is correct and usable in written English.
It can be used when discussing the strong or effective coordination or agreement between different elements, such as ideas, strategies, or teams.
Example: "The success of the project relies on a robust alignment of our marketing and sales strategies."
Alternatives: "a strong coordination of" or "a solid agreement of".
In silico analysis of the C. elegans genome identified 33 putative globin genes in this species using a robust alignment procedure based on conserved structural features of the classical globin fold.
We designed a robust alignment procedure based on a mixed structural and sequence multiple alignment of manually delineated ACD regions.
The accurate and robust alignment of the cavities is achieved by applying lithographically precise micromachining to form through-etched alignment holes in the mirror chips.
Species-specific primers were designed to fall in regions of robust alignment between all members of each group so that tests of tissue-specific patterns of expression were inclusive of all transcripts and were therefore conservative.
Exclusion of the 13 non-mycobacterial sequences produced a much more robust alignment.
This method generated a robust DNA sequence alignment of both distantly and closely related species, as direct DNA sequence alignment may produce unreliable alignments by introducing many indels (gaps).
Then, they used robust alignment algorithm to choose the best subset of matched points against incorrect matches and multiple matches.
Protein sequences were modeled using the I-TASSER server, using robust alignment procedures followed by simulation and refinement of subsequent models [46].
A significant bottleneck in the analysis of these sequences is the generation of a robust multiple sequence alignment (MSA).
PhyloPhlAn generates highly robust phylogenetic trees from a concatenated alignment of a computationally selected subset of amino-acid sequences from 400 most conserved universal proteins following a maximum likelihood maximization approach using RAxML [ 64, 65].
