We report that The Ethnologue classification provides a better genetic proxy than Greenberg's classification at the stock and at the group levels.
Though The Ethnologue classification provided a better genetic proxy than Greenberg's classification, some linguistic families were not perfectly characterized in terms of genetic clustering.
The ELN classification was a better predictor of posttransplant outcomes compared with classifications that use only cytogenetic data.
This study was aimed at assessing whether reclassification of subjects with type 2 diabetes from the Renal Insufficiency and Cardiovascular Events (RIACE) Italian Multicenter Study using the AKDN alternate system or the new KDIGO classification provides a better definition of burden from CVD and diabetic retinopathy (DR) than the NKF's KDOQI classification.
This classification enables a better comparison of related research.
Within this subgroup, only the inverse correlation with amplification of CCND1 was observed, suggesting an accurate classification and a better representation of CHK1 deleted tumors.
We conclude that the 5th edition of the TNM classification provides a better estimation of prognosis, however, examination of at least 15 negative regional lymph nodes is too high a threshold and 5 gives similar prognostic value.
Using Boolean interaction Cox-regression models to identify non-linear pathway combinations associated with clinical outcome, we show that simultaneous high activation of Th1 and low activation of a TGF-beta pathway module defines a subtype of particularly good prognosis and that this classification provides a better prognostic model than those based on the individual pathways.
Identification of their interactors (protein, RNA, promoters, 3D structures, other structures of the chromatin) will allow a more functional classification and a better understanding of whether these RNAs can be considered genes, because of their potential role as regulatory nuclear RNAs.
In particular, both RR and DET are selected in the optimal sets of 4 and 5 input sets using MLPs, together with the above mentioned features (size and STD y ), indicating the importance of including the considered nonlinear information to improve classification (reflecting a better description and characterization of pupil dynamics).
