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The isospectral renormalization group is a powerful method to analyze the spectrum of operators in quantum field theory.
MSA is the most powerful method to analyze the genetic sequences and most of state-of-art algorithms are constructed based on it [14] [16].
This is a very powerful method to analyze a monotonic trend in nonlinear data.
Like ANM-NMA, EDA constitutes a powerful method to analyze collective motions in biomolecules.
There is also no uniformly most powerful method to analyze omics data and the use of various approaches to infer biological interactions requires modeling expertise [ 39].
Genetic cell lineage tracing is a powerful method to analyze such lineage relationships between two different types or between more than two types of cells.
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The complexity of modern engineered surfaces requires the development of very powerful methods to analyze and characterize them.
K-means clustering [ 2, 11] is considered to be one of the most powerful methods to analyze behavior of gene expressions between dependent experiments, such as samples taken over a course of time from the same culture.
Targeted expression by the Gal4-UAS system is a powerful genetic method to analyze the functions of genes and cells in vivo.
The RP approach is a powerful statistical method to analyze microarray data generated from relatively few replicates, performed in different laboratories and/or using different platforms.
Canonical correlation analysis (CCA) is a popular and powerful dimensionality reduction method to analyze paired multi-view data.
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