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The problem is that current methods require far more energy than can be produced, at an eye-watering cost.
Ligand-based methods require far less protein than protein-based methods and are not limited by the size of a protein.
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The method requires far less samples than both crude Monte Carlo simulation and the cross-entropy-based adaptive importance sampling method employing a unimodal density function; thus achieving relatively small values of the coefficient of variation efficiently.
Computational methods for function recognition require far less time and expense and so can augment experimental methods.
As Table 1 shows, the energy-based methods (ODF E and ODFELP) require far less computation than any of the others.
Such a system would probably require far less computation than current methods, thereby helping to conserve a rover's precious battery power, Kleinfeld says.
We, therefore, have to resort to a sophisticated optimization method, which requires far less computation.
So far, the reference method and all the alternative methods require a pre-enrichment step lasting 24 h to several days.
The methods require different microbial partners, though some of those partners, such as the yeast used in beer brewing, Saccharomyces cerevisiae, are used far and wide.
Conventional DNA sampling methods require at least 200 cells.
Indeed, all phylogenomic methods require significant financial resources, but when factoring in the costs of reagents, sequencing, and labor versus the number of nucleotides sequenced, target enrichment type methods are far less expensive than traditional PCR-based methods [ 9].
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CEO of Professional Science Editing for Scientists @ prosciediting.com