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To test this prediction, we first utilized computational methods to predict conserved fRNA secondary structures within multiple species alignments of Saccharomyces sensu strico genomes.
We therefore utilized computational methods to test the hypothesis that some of the genes within this large up-regulated cluster are co-ordinately regulated by common transcriptional mechanisms.
Systematic screens for sRNAs have focused mostly on intergenic regions and utilized computational methods [ 5– 10], shotgun cloning strategies [ 11, 12] and high-density oligonucleotide probe arrays [ 13– 15].
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As these mutations were not reported in earlier studies, we further characterized the effect of these mutations on the protein function and stability utilizing computational methods such as SIFT, Polyphen, and MD simulations.
CAMM also utilizes computational linguistics methods for comparison of clinical annotations from multiple datasets.
Although this homology-based method remains the most widely utilized computational tool for function assignment, some proteins identified from genome sequencing do not have any homologs that were functionally characterized in the previous studies.
We utilized computational approaches to identify new candidate recruiters.
This study utilizes computational topology optimization methods for the systematic design of optimal multifunctional silicon anode structures for lithium-ion batteries.
Our current research effort focuses on full-length three-dimensional structures of the R-subunit, utilizing computational and bioinformatics methods.
The framework utilizes novel computational methods which enable evaluating the model fragility with respect to quantitative performance measures and parameters such as reaction rate constants and initial conditions.
Our method utilizes computational predictions of protein-ligand binding across the human proteome.
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