Papers [39] and [40] introduced the TEF based method for analyzing and characterizing the power system oscillations.
Specifically, we introduce a distributed-cognition based method for analyzing representational activity in terms of the movement of information across media, which enables us to systematically explore the space of potential interactive mechanisms.
TruHMM differs from an earlier HMM based method for analyzing transcriptomes in B. anthracis[ 94] in the several important aspects, and overcomes its shortcomings.
The first part of our model is a biophysically-motivated k-mer based method for analyzing PBM data, which allows secondary binding profiles and nucleotide dependencies in different positions of the TF binding sites.
Mass spectrometry (MS -based MS -basedor analyzing protein higher order structures have gained increasing application in the field of biopharmethodscal development.
For these reasons, it is desirable explore complements to tree-based methods for analyzing and displaying DNA sequences from large numbers of organisms.
We compared mRNA-based and ICC-based methods for analyzing the presence of DTCs in 313 BM samples from 271 breast cancer patients.
Principal components analysis (PCA -based methods for analyzing PCA -based structure, like EIGENSTRAT (Price et al. 2006) and Smethods (Patterson et al. 2006), construct low-dimensional projections oforhe danalyzingmaximally retain the variance-covariance structure among the sampopulationpestructure
To provide a baseline for comparison, we also analyzed our simulated datasets with two linear regression based methods for DE and DV patterns discovery.
For data with high dimensionality, the commonly used multivariate normal model rarely fits the actual data, and the nonparametric method is not directly applicable in cluster analysis, so neither of the above models based or non-model based methods are suitable for analyzing the dependence and high dimensionality of family data.
This makes SVM based methods a unique tool for analyzing proteins with very low sequence similarity.
