Sentence examples for substantially different methods from inspiring English sources

Deploying substantially different methods than used previously, their new estimates were remarkably similar to the earlier estimates.

We believe that the use of substantially different methods may allow more consistent results and verification of negative results.

Although both approaches are based on published data linking the gene products of our top hits in functional annotated pathways, they use substantially different methods.

They remove reliance on extrapolating from studies of outbreaks, subgroups, or other countries, which may use substantially different methods and settings.

This work involved developing efficient algorithms for a weighted parsimony model of copy number evolution, which required substantially different methods than the unweighted model in (Chowdhury et al., 2014).

To conclude, these studies show that despite using substantially different methods and genes, classifications within GSE4732_p1 or GSE4475 represent a largely consistent definition of BL that can be used as a basis for a classifier that uses fewer genes and transfers well between the two data sets.

Psychiatric diagnoses were based on clinical ratings of interviews, including extensive open-ended comments – a substantially different method than the respondent-based YSI measure of positive attributes.

In our previous work, Zhang et al. proposed to model differential dependency networks between two conditions by detecting network rewiring using significance tests on local dependencies across conditions [ 13],[ 14], which is a substantially different method from the one proposed in this paper where experimental data and prior knowledge are jointly modeled.

Prevalence of vertebral fractures differed substantially by the different methods, so standardization is crucial for patient care and for large scale epidemiological studies.

While the overall objective of learning a continuous vector space representation for each word based on its textual context remains, the underlying algorithms are substantially different from traditional methods such as LSA and RI.

Our major theoretical results include algorithms, substantially different from prior methods (Chowdhury et al., 2014), to construct weighted parsimonious sequences of single gene gains/losses, whole chromosome gains/losses, and whole genome duplications so as to infer the distance between configurations of gene copy numbers between any pair of cells.