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The methods described above belong to a class of static methods and presumes that positions of inclusions are fixed after synthesis.
However, as the number of solved static structures increases in the PDB and the performance of static methods does not reach desirable levels, the importance of sampling the conformational space of the molecules becomes more apparent.
Results obtained by these dynamic methods compared those of static methods, simple pairwise methods, Audic-Claverie statistics and Fisher's exact test, and pooling static methods, glmFit in edgeR, LIMMA, and log linear model as shown Figure 3.
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In our study, using the modified assumptions, RNA-seq time series with short time period (4~8 time points) and single observations as gene-by-gene approach are applied to compare the performance of AR(1) model to static methods in identification of differential expression.
There exist a number of research projects that focus on precision analysis, most of which are static methods that operate on the computational flow of the design and uses techniques based on range and error propagation to perform the analysis.
That is, most of temporal genes at low and moderate expression levels are detected as significant genes in dynamic methods, whereas, due to power issues of parametric static pooling methods and simplification of pairwise methods, static methods do a good job at high expression levels.
A common shortcoming of all pure static methods is their inability to detect dynamically loaded threats, e.g., when the analyzed file does not contain attack code but instead loads it over the network or from another file.
The purposes of this paper are to (i) present a brief review of dynamic compression and its affects on materials, (ii) review considerations that led to the sample holder designed specifically to make metallic fluid H, and (iii) present a brief inter-comparison of dynamic and static methods to achieve high pressure relative to their prospects for making metallic H.
Consistently, HMM, SETI, and AR(1) model that account for time dependency Markovian property in the models identified more of statistically significant TDE genes than static methods regardless of expression levels.
Static pushover analysis is one of the non-linear static methods used for analyzing structures subjected to seismic loads.
The results show that dynamic FER can offer much higher recognition accuracies than traditional static methods of FER.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com