Sentence examples for minimum error correction from inspiring English sources

The minimum error correction (MEC) model is an important computational model for haplotype reconstruction problem.

The minimum error correction (MEC) model is an important computational model for an individual haplotype assembly problem.

The minimum error correction (MEC) model is one of the important computational models for single individual single nucleotide polymorphism (SNP) haplotyping.

Known computational model of this problem is minimum error correction (MEC) that has been proved to be NP-complete by Lippert et al., but there are few practical algorithms for it.

The SIH reconstruction problem can be formulated as bi-partitioning the input SNP fragment matrix into paternal and maternal sections to achieve minimum error correction (MEC) time; the problem that is proved to be NP-hard.

The main models are MEC (minimum error correction) [ 24], MFR (minimum fragment removal), and MSR (minimum SNP removal) [ 13].

One interesting aspect of Shannon's proof of a limit for minimum average error correction length is that it is nonconstructive; that is, Shannon proved that a shortest correction code must always exist, but his proof does not indicate how to construct such a code for each particular case.

In particular, nonsynonymous substitution P1606S was observed within the CD8+ T-cell epitope 1602RAQAPPPSW1610 at low frequency at 44 DPI but this mutation was not detected at 57 DPI, most possibly because it was at a frequency of occurrence lower than 1% (the minimum threshold detected after error correction of sequencing data).

Where the code (45,33) is also capable of correcting any single error burst of length 3 or less by Remark 4. Table 5 gives comparison between minimum distance, code rate and error correction capability of codes C 15, C 45 in (F_{2}left [x;2mathbb {Z}_{geq 0}right ]), (F_{2}left [x;frac {2}{3}mathbb {Z}_{geq 0}right ]), respectively.

The minimum distance is closely related to the error correction capacity of the code; a code of minimal distance corrects any error vector of weight at most ; that is, it is possible to recover the original codeword from any, with.

Tibshirani and Tibshirani [31] propose a bias correction for the minimum error rate in cross-validation which does not require additional computation.