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It outperforms a set of 13 contemporary blockiness methods in terms of prediction accuracy and monotonicity.

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Both methods combine interaction and expression data and have been proven to outperform a set of earlier methods that use only one of the data sources in the task of finding gene modules.

It remains unclear whether open NIV-NAVA outperforms a setting that includes externally applied PEEP.

Furthermore, the model outperforms a wide set of alternatives, such as its previous version and MIDAS regressions, although not a specification including also hard data.

Our methods outperform a representative set of earlier models in the task of finding biologically relevant modules having enriched functional classes.

NSAG-II is one of such EAs and it outperforms others in terms of finding a diverse set of solutions and converging near the true Pareto optimal solutions.

Empirical evaluation shows that the resulting information-sharing multi-component algorithm significantly outperforms other solvers on a set of "hidden" instances, i.e. instances not available at the algorithm design phase.

(these coders perform considerably better than the standard JPEG. AGU [36] and ADCTC [37] outperform JPEG2000 [38] on a set of standard test images. Compression parameters for these three coders can be easily varied. There are automatic procedures that allow reaching OOP for them [25, 26].

Tests of the derived potential function on commonly used decoy sets illustrate that it outperforms most of the existing coarse-grained potentials in terms of its capabilities in recognizing native structures and consistency in achieving high Z-scores across decoy sets, and it has almost equivalent performance to the potentials which considered complex intra-molecular interactions.

It outperforms its counterparts on a whole host of measures from patient satisfaction to waiting times.

This algorithm has been checked on a set of 153 benchmark instances with known optimal solution and it outperforms the results obtained with previous ATSP heuristic methods.

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