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Nanopore sequencing, hailed as a more portable and affordable way to analyze DNA than previous methods, works by measuring changes in electrical current as single nucleotides pass through a pore not much bigger than DNA itself.
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In Fig. 4, each figure shows how the sparse speaker adaptation methods work by EPL1 and SNEP.
The CS methods work by substituting a component of the (transformed) MS image, C l, with a component, C h, from the PAN image.
These survey methods work by partitioning the study area in some way, into strata, or primary sample units, or in the case of adaptive cluster sampling, into networks.
These methods work by partitioning the image domain into different subregions with the assumption that each subregion is homogeneous with respect to some characteristics such as intensity [21, 22, 31].
Homogenization or density-based topology optimization methods work by distributing a fixed amount of material to the most effective areas of the design domain so as to create an optimal structural configuration that meets the minimum compliance criteria.
Typical HMM-based methods work by representing an MSA as a form of directed acyclic graph known as a partial-order graph, which consists of a series of nodes representing possible entries in the columns of an MSA.
Multidimensional Scaling (MDS) methods work by finding a set of axes that minimize the "stress" between the original distance matrix and the distances between the plotted sequences [35].
Both methods work by allowing the actin cytoskeleton to engage in CME in mitotic cells.
Instead of eliminating irrelevant genes, feature extraction methods work by transforming the original data into a new representation.
Deconvolution methods work by estimating and then removing the contribution of light both from out-of-focus fluorescence and from in-plane spreading of light due to diffraction.
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