Sentence examples for conventional selection methods from inspiring English sources

Sequence analysis showed a wide range of amino acid changes not detected by conventional selection methods using laboratory-derived strains.

Conventional selection methods involving either radioactive labeling of RNA or the use of label-free methods such as SPR to track aptamer enrichment require resources that are not widely accessible to research groups.

Despite the large size and complex structure of antibodies, recent findings suggest that antibody solubility can be dramatically improved using rational design methods in addition to conventional selection methods.

Alternatives to these conventional selection methods will be required to overcome these limitations.

Conventional selection methods have been shown to be successful in breeding crops with improved P use efficiency.

However, a systematic comparison of the loss of favourable and rare alleles between genomic and conventional selection methods as selection proceeds is lacking.

It can be noted that in conventional feature selection methods, features or subset of features are selected based on the rank as obtained by evaluating features against a selection criterion such that redundancy of features in the training set is minimized.

Unlike conventional solvent selection methods, which employ empirical or experimental parameters, the present work proposes a novel solvent screening method using theoretical descriptors to quantify solvent effects.

The new lag selection criteria we propose are shown to avoid this problem yet deliver unit roots with almost identical finite sample size and power properties as the corresponding tests based on conventional lag selection methods when the shocks are homoskedastic.

Some of the recent approaches that attempt to improve the performance of the conventional feature selection methods use the ideas of neighborhood margins [44 46], and manifold regularization using SVMs [47].

Conventional feature selection methods apply multiple level processing on a given feature vector to find a subset of useful features for classification using several machine learning techniques and search strategies.