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With the feature selection approach based on the mRMR method and IFS procedure, we found that the following seven features would play the major roles in determining the stability of proteins: KEGG enrichment scores, subcellular locations, polarity, amino acids composition, hydrophobicity, secondary structure propensity, and the number of protein complexes.
These criteria are associated with the probabilistic reaction rate (propensity) and the number of molecules that participate in the reaction.
> -wrap-foot> Daytime sleep propensity and the number of sleep onset REM periods at the MSLT were also stable, whereas the 24 h total sleep time decreased from first to follow-up evaluation (P = 0.004, Fig. 1) as the final result of the (non-significant) decreases of daytime and night-time sleep.
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It was revealed through our analysis that the following seven characters played major roles in determining the stability of proteins: (1) KEGG enrichment scores of the protein and its neighbors in network, (2) subcellular locations, (3) polarity, (4) amino acids composition, (5) hydrophobicity, (6) secondary structure propensity, and (7) the number of protein complexes the protein involved.
As we can see from Figure 3, the following seven kinds of features play the major roles in affecting the protein stability: (1) KEGG enrichment scores, (2) subcellular locations, (3) polarity, (4) amino acids composition, (5) hydrophobicity, (6) secondary structure propensity, and (7) the number of protein complexes.
This study investigates the association between the propensity to seek care and the number of GP visits on patient level and the association between a population's propensity to seek care and rates of avoidable hospitalization at country level.
Interestingly, a significant positive correlation was found between the propensity for low expression and the number of miRNA target-site types in each group (Spearman's rank correlation, Rs > 0.7, P < 0.05, N = 8).
The loss of genetic variability could affect reproductive traits, such as the propensity of individual to mates and the number of offspring in Drosophila simulans [47].
The differences in PVFP by demographic reflect the differences in average earnings, the propensity to be in the workforce, and the number of years expected to remain in the workforce.
This article studies the statistical relationship between the search propensity of suicide-related terms on Google and the number of suicides.
19As we will explain in the next section, we were not able to include all of these variables in the propensity score because the number of observations drops substantially.
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