Sentence examples for more sensitive algorithms from inspiring English sources

High coverage genes require more selective methods, whereas low coverage genes favor more sensitive algorithms.

More sensitive algorithms return larger numbers of ccgs because they can detect low-amplitude rhythms.

As more sensitive algorithms for deducing homology become available, it may be possible to confirm or refute the relatedness of the tethering complexes and distinguish between these scenarios.

Later, the gene set enrichment analysis (GSEA) method [ 11] pioneered another family of more sensitive algorithms based on testing the distribution of functional annotations along a list of genes ranked by differential expression [ 12- 16].

More complete genome assemblies, or improved and more sensitive algorithms, might detect sequence conservation at these enhancers; while we cannot rule out this possibility, our results were obtained with the best assemblies and computational tools available at the time.

We used hot pixels detected with the more sensitive Algorithm 2. It purports to detect a fire of 0.1 ha if it is hotter than 327°C.

A more sensitive algorithm that treats control as a time varying covariate would most likely provide a more accurate evaluation of control status.

Therefore, the present surveillance used a more sensitive algorithm to capture pneumonia cases, while the previous surveillance captured only inpatient cases, encompassing more severe cases.

These programs first find sub-strings called seeds that exactly match in both the reads and the reference sequences, and then extend the shared seeds into longer, inexact alignments using a more sensitive algorithm that allows for mismatches or gaps.

In addition, the BDGP Splicing program predicted that the variant causes a complete loss of the donor site for exon 35 splicing, although this was not predicted by SpliceSiteFinder, consistent with the more sensitive algorithm of the BDGP splicing program [ 37].

Therefore, the higher repeat coverage reported herein is likely due to two main factors: the use of a more sensitive algorithm to identify repetitive regions (RepeatMasker versus BLAST in [ 2]) and the discovery of two novel TE families (ERE1 and ERE2) based on intra- and inter-species sequence comparison.