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Bioinformatics methods have expanded in recent years to include searches for genetic interactions, yet many challenges remain in these analyses including extensive computational and time requirements as well as a high penalty for correction of multiple comparisons when exhaustively testing pairwise combinations of all genome-wide SNPs.
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Sophisticated tabulation methods have expanded what researchers can do.
The utilization of multiple mass spectrometry methods has expanded the diagnostics and characterization of glycosylation.
As a result, the breadth of applications of the method has expanded.
Meanwhile, new bioinformatics methods have been developed for inferring protein function using associative analysis of functional properties to complement the traditional sequence homology-based methods.
Many bioinformatics methods have been developed for predicting new AMPs.
Currently, bioinformatics methods have been used to decipher target genes in several studies [ 47, 48].
Bioinformatics methods have been developed and tested over the past decade that distinguish disease-related nsSNVs from neutral polymorphisms [ 1- 11].
To this end, a few state-of-the-art bioinformatics methods have been developed to predict T3SEs (12 19).
To date, several in silico bioinformatic methods have been developed and applied [ 2, 3].
New methods and data have expanded these applications.
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CEO of Professional Science Editing for Scientists @ prosciediting.com