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This method uses sequence homology between the protein of interest and a protein whose 3D structure is known to predict a three-dimensional model.
The EnzymeDetector [ 6] annotation method uses sequence similarity analysis and a comprehensive enzyme database, BRaunschweig ENzyme DAtabase (BRENDA) [ 7], which is manually extracted from the literature.
For a given drug, our method uses sequence order independent structure alignment, hierarchical clustering and probabilistic sequence similarity to construct a probabilistic pocket ensemble (PPE) that captures promiscuous structural features of different binding sites on known targets.
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The PeakPicker ASE method uses sequencing trace data to quantify the relative fluorescent intensity for both alleles at heterozygous SNPs.
Simulation of method using sequences of random numbers.
The results are a little worse than the two-pass method using sequence-level adaptation, but generally better than the static approach.
Most methods used sequence alignments with an underlying hypothesis that sequence similarity is correlated with functional similarity.
Established methods use sequence or structure similarity to infer functions but those types of data do not suffice to determine the biological context in which proteins act.
These methods use sequence templates [ 7] and profiles of the sequences [ 8] as features.
Other methods use sequence quality information derived from the raw trace data.
These methods use sequence similarity to associate reads with taxonomic ranks.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com