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We used CLC Assembly Cell as the assembler, which is known as a short-read assembler and has been used for a benchmark sequence comparison [ 22].

{mathbf{x}}_{mathbf{i}}^{left(mathbf{0}right)}left(mathbf{k}right)=left({x}_1^{(0)}(1), dots {x}_i^{(0)} k)right) (2 where k = 1, 2, …, K. ( {mathbf{x}}_{mathbf{i}}^{left(mathbf{0}right)}left(mathbf{k}right) ) is used as a benchmark of sequence selection if the original sequence satisfies normalization, scaling, and polarization conditions.

Scaled delta-distance, defined above as δ*√ n, is a statistical invariant for any benchmark sequence generated by a Markov chain exhibiting the same signature as the given sequence.

A sequence-based method is often designed on a benchmark dataset, sequence features such as amino acid composition [19], pseudo amino acid [20] (PseAAC), are used to represent the data (e.g. protein sequence), then a prediction model can be built according to the machine learning algorithm (e.g. nearest neighbor algorithm).

For a given query sequence, we ignored its self hit but counted as a homolog (true positive), any benchmark sequence belonging to the same SCOP superfamily, and as a non-homolog (false positive) any benchmark sequence belonging to a different SCOP fold.

In other respects, this dataset is ideal as a benchmark, as the 454 sequences stem from the same individual on which the reference is based while the reference was constructed using a separate sequence set.

This collection of spidroin sequences can serve as a benchmark for the quality of the transcriptome and the capacity of the assembly to successfully integrate the large repetitive regions, where de novo transcriptome assembly has traditionally struggled [ 45, 46].

To prevent proximity in sequence from biasing results, only positions 10 or more apart in sequence are considered when using contact as a benchmark.

As a benchmark, we used 20,000 publicly available turkey BAC-end sequences (BES) (Table 3).

As a benchmark for our metagenomic assemblies we separated the reads by their source sequence and performed isolate assemblies.

We used our dataset as a benchmark to assess the performance of several statistical methods to cluster sequences into molecular operational taxonomic units.

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