Our comparison process relies on four steps (gene list analysis, simulations, spike-in data and re-sampling) to formulate comprehensive and robust conclusions about test performance, in terms of statistical power, false-positive rate, execution time and ease of use.
More importantly, the present findings, based on a representative sample, can be used to formulate hypotheses for populations with similar demographic and cultural characteristics, low socioeconomic status, and living in an underdeveloped country.
However, the retrospective nature of most of the studies and the small sample sizes make it difficult to formulate a clinically useful prediction rules regarding allogeneic RBC transfusion.
To develop a powerful method for predicting protein subcellular localization, it is very important to formulate the sample of a protein in terms of the core features that are intrinsically correlated with its localization in a cell.
As stated in a recent comprehensive review [20], to develop a powerful method for statistically predicting protein subcellular localization, one of the most important things is to formulate the sample of a protein with the core features that have intrinsic correlation with its localization in a cell.
The most straightforward way to formulate the sample of a conotoxin peptide P with L residues is to use its entire amino acid sequence, as can be formulated by (3) P = R 1 R 2 R 3 R 4 ⋯ R L, where R1 represents the 1st residue of the conotoxin peptide and R2 the 2nd residue of the peptide and so forth.
Actually, using the FunD information to formulate protein samples for statistical predictions was originally proposed in [51], [52], and quite encouraged results were achieved.
Using FunD to formulate protein samples was originally proposed in [32], [33] based on the 2005 FunDs in the SBASE-A database [34].
In order to formulate protein samples of different sequence lengths with vectors of a uniform dimension, let us adopt the concept of pseudo amino acid composition (PseAAC) [24], [26], [27].
However, many of these studies did not use large or representative samples, which make it difficult to formulate concrete conclusions that are representative of the complete population with hearing loss.
