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In this study, we proposed a novel approach for binding sites identification in proteins, which not only integrates local features and global features from protein sequence directly, but also constructed a balanced training dataset using sub-sampling based on submodularity subset selection.
In correspondence with the MathML community, we agree that there is no single semantic approach for binding MathML into declarative programs, and MathCML takes a pragmatic approach with a certain amount of implicit semantics which will be natural to the physical scientist.
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Phage display is a powerful approach for establishing binding preferences of peptide binding domains and in extension to discover novel motifs.
One of the limitations of the most common approach (searching for binding site clusters), is that varying parameters window size, number of sites, cutoff positional weight matrix score often results in widely divergent predictions.
We developed an alternative approach for controlling binding specificity based on computational protein design.
Results: We tested this hypothesis using a multi-evidence approach for predicting binding sites.
We implemented a two-stage cascaded classification approach for CaM binding prediction.
Using a global fitting approach for 1 1 binding between IC3-C58 and an S100B protomer, changes in chemical shift were fit simultaneously to eq 1 to obtain a Kd of 274 ± 58 μM.
In the following sections, we explore two recent studies from our laboratory that have harnessed the DNA curtain approach for measuring binding distributions, and we illustrate the usefulness of the conceptual framework presented above as a lens to interpreting these types of experiments.
To deal with this issue, we propose in this paper an agent-based approach for synchronizing bindings of Web services to maintain their consistency and sustainable use.
As the number of available protein structures increases, structural alignment based algorithm becomes the dominant approach for protein-binding sites prediction.
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