Sentence examples for most probable predictions from inspiring English sources

Each docking method returned the 100 most probable predictions out of thousands of candidates based on geometry, hydrophobicity and electrostatic complementarity of the molecular surface.

Applying strict selection criteria, we chose the eighteen most probable predictions of novel alternative splicing events for validation experiments with RT-PCR.

This method is based on the subsurface model, which is considered the most probable prediction (best guess).

For each prediction for domain di, ngLOC outputs two confidences scores: CS di) – a confidence measure for the most probable prediction, and MLCS di) – a confidence measure for the likelihood that di is localized into multiple organelles.

The output PDB file contains the desired number of models (between 1 and 300) ranked as the most probable prediction candidates according to the scoring function used by the program.

The ad-hoc quantity based on the second order rate of change in the log probability (ΔK) showed a clear peak at K = 5, which confirmed that a K value of 5 was the most probable prediction for the number of subpopulations.

Ambiguous sites were confirmed by cross-referencing (by sequence, charge, and quantity of residue modifications) with most probable site predictions from MaxQuant (version 1.0.13.8 in singlet mode, same Mascot settings) [ 140].

Such inferences reflect the most probable or likely predictions without additional information/processes assumed.

For the correct elimination of duplicates and choice of the most probable structure the prediction of 13C NMR spectra and the calculation of the average deviations of the calculated spectra from the experimental data is used in the StrucEluc system.

The imposition of the requirement that the prediction must be strong enough, i.e. that the difference between the probability of the predicted (most probable) state and the probability of the second most probable state must be larger than a certain minimum value also improves significantly secondary structure predictions.

The implementation contains two options for prediction: 1) Prediction using the local regression model calibrated in the most probable cluster, and 2) Prediction using a weighted sum of the local regression models, using the estimated cluster membership values as weights.