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The discordance with ESEfinder may be associated with differences in the respective analytic methods, as several of the models (SF2/ASF, SC35, SRp40) used by ASSA and ESEfinder were created from the same source of experimental data.
It is possible that franchisee reports of provision of short-acting methods are underreported compared with long-acting methods, as several social franchising programs include voucher programs aimed at reducing barriers to accessing more expensive LARCs; thus, there are direct incentives to report all LARCs provided.
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We found very little overlap between the different screening methods, which underlines the importance of using several complementary methods, as well as several environmental conditions, to attain a comprehensive analysis of bacterial sRNAomes.
We will first show a mini example which involves an initial implementation of our methods as well as several interesting test cases in this section.
These included exons identified by either of the two profiling methods, as well as several exons previously identified as PTBP1 targets.
This is expected and can be considered as a benchmark result for our method, as several other pathway-based studies in cancer have observed similar results [ 51- 53].
Numerical solution of the model equations with the finite element method, as well as several examples of application of the model for analysis of various problems, are presented in the part 2 paper.
In this section, we introduce several conventional methods as below.
The proposed method was compared to several existing methods as well as permutation testing (the gold standard) by simulation studies.
For MDD+suicide group, one hundred and seventy-one patients (79.5%) suicided by drug overdose, hanging, drowning and 44 patients (20.5%) suicided by violent methods such as several deep cuts.
In Section 3, we demonstrate the effectiveness of our methods on several artificial datasets as well as experimental data from two microbial genomes.
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