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Two models predict either long (>30 residues) or short (<15 residues) disordered regions based on features similar to those used by VL-XT.
Two models predict either long or short disordered regions – greater or less than 30 residues – based on features similar to those used by VLXT.
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Towards this, it extracts pairs of similar stems based on features like helix length and so on discussed above.
Sequences were sorted into homoeologues based on features specific to the homoeologue most similar to that of T. occidentale, enabling SNP identification.
Algorithms based on features usually extract significant and stable features.
An algorithm based on feature-vector computation over AST was applied by Lee et al. ([2010]) to detect similar clones.
Although it is acknowledged that the data used in the current study were collected prior to the development of a new playground at the park in the low SES area, the comparison park in the high SES area was selected based on having similar features and amenities to that of the intervention park at baseline.
To circumvent these limitations, feature-based models have been constructed to distinguish essential genes from non-essential ones based on common or similar features among essential genes [ 24- 28].
In the computer simulations of our previous studies, we have found that the Ka/Ks-calculating methods based on similar substitution models (capturing similar evolutionary features) often yielded similar results [ 23, 75].
Our model proves the concept that the needed extent of PLND is dependent on and can be predicted by the risk of LNI based on individual patient features, similar to a model we previously described for PCa (Kluth et al, 2013).
This observation fits with known signatures for effectors and other proteins clustered with these known effectors based on similar sequence features may represent candidates worthy of further investigation.
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