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Multiple sequence clusters are inferred to represent occupants of distinct niches or, alternatively, the mixing of two physically separated populations.
Even though multiple sequence clusters were identified with single nucleotide variations, most of them were polymorphic within a germplasm line at many loci.
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Multiple sequences clustering into the same subfamily were designed by an additional number (1-2).
Further investigations indicated that the multiple sequences clustering within branches A, B and C are different alleles of the same locus.
The full nomenclature included two letters for genus and species, followed by PDIL and by an Arabic number indicating the corresponding phylogenetic group; multiple sequences clustering into the same subfamily were designed by an additional number (1-3).
Multiple sequence alignment, clustering, assembling and the generation of consensus were accomplished by StackPACK [ 29].
Our comparative analysis revealed multiple highly conserved sequence clusters that have undergone a cumulative evolutionary divergence of >150 million years [ 8].
Both resources exploited powerful sequence profiles – known as Hidden Markov Models (HMMs) – which were built from multiple alignments of sequence clusters in domain superfamilies and used to recognize domain relatives in the genome sequences.
The construction of a large supermatrix involves a number of computationally challenging steps including, but not limited to, database operations, BLAST comparisons, sequence clustering, multiple sequence alignment, and combining data sets.
Analysis of transposases was performed by multiple sequence alignments and clustering methods followed by dendrogram construction to set up clusters of related proteins (see Methods).
We conducted multiple sequence alignments for clustered contigs from each group (contig with only one gene and contig with multiple genes) using ClustalW [ 36].
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