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The performance of such a comparison or alignment method is measured by its ability to predict the degree of similarity between pairs of proteins, and to produce a rel- ative ranking of similar (positive) and dissimilar (nega- tive) pairs. The fraction of correctly classified positives (true ...
from the geo database . differential analysis was then performed on these datasets. the overlapping degs generated from these two sets were further analyzed, and a degree-based ranking was used to identify 10 hub genes (rps27a, rpl5, rps8 , rpl4, rps2, rpl30, rpl23a, rpl31, rpl26 ...
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Since the smaller mean of re-ranking scores represents better performance, we used the box size = 0.2 and z-score > 0 as default parameters to build SINUM SCNs in this study. Fig. 2 Clustering performances of DMs and GEMs on seven scRNA-seq datasets. A Distributions of ranking/...
Figure 9.PPI network construction and analysis of subtype B.(A) The PPI network of the 24 hub genes. (B) MCC ranking based on the degree of nodes. (C) The top ten genes ranked by MCC, exhibit an increase in MCC scores as indicated by the deepening color. ...
whereDis the parametric uncertainty measurement considered,Nis the size of the binding sites,qis the Rényi order andHmaxis the maximum entropy for the set of probabilitiesp(X) andp(y), see section “Database description”.Cis a value between 0 and 1. WhenCis close to 1, the degree of ...
Note that the cosine distance generates values ranking between 0 and 1. The similarity value can be considered as a description of the functional relationship between these terms, whereby similarities equal to 0 stand for unrelated terms and 1 stands for strongly related. The similarity matrixSis ...
(F) Venn diagram for identifying hub genes among different ranking methods. Full size image The expression of hub genes In order to identify the genes necessary for the co-occurrence of DCM and DFU, we verified the expression of the hub genes of DCM (GSE 197,850, Fig. 4A) and DFU (...
Candidate feature ranking To rank the contribution of each feature to the efficiency of sgRNA design, we fitted a logistic regression model within each dataset using the binary sgRNA efficiency indicator as the response and the features as predictors. The Bayesian Information Criterion (BIC) for the...