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Compound models were built and refined using coordinates and topologies generated by PRODRG (Schuettelkopf and van Aalten 2004).
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Complementary compound models are constructed by considering the maximum of a sequence of i.i.d.i.d
The compound model is then used to decode the sequence with Viterbi algorithm.
In order to see how the accumulation of receptors over time affects the receptor signal elucidated by glutamate a compound model is created comprising AMPAR incorporation into the PSD with glutamate release and binding to synaptic AMPAR.
Similarly, RW and WW compound channel models were also developed.
Unstructured patterns or compound symmetry models were applied, depending on the outcome of the difference in the -2log likelihood of the two models.
Per compound, multilevel models were fitted with either POPs total exposure from conception to 24 months or prenatal or postnatal exposure.
For 60 aromatic compounds, two models were found to give good estimate of kOH (r > 0.735; Table S9).
However, the performance progression on the HTSFP subsets for label and compound removal models is very similar.
Different covariance pattern models were tested, compound symmetry, heterogeneous compound symmetry, first order autoregressive and heterogeneous first order autoregressive models.
However, despite the immense number of investigations carried out on these compounds, no detailed molecular models were proposed for them.
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CEO of Professional Science Editing for Scientists @ prosciediting.com