Sentence examples for multifactorial likelihood model from inspiring English sources

The multifactorial likelihood model described by Goldgar et al. [ 3], considered UVs with overall odds of causality >1000 1 (LR>1000) as pathogenic and those with odds of causality <1 100 (LR<0.01) as neutral.

These findings have also served as the basis for including independently predictive tumor histopathological features as a component of the multifactorial likelihood model for clinical classification of BRCA1/2 variants of uncertain significance [ 25].

Our findings provide measures of confidence in the individual LR estimates, and in particular, allow age at diagnosis to be incorporated into the pathology component of the multifactorial likelihood model.

Multifactorial likelihood models incorporating a range of information therefore have been developed to enable predictions to be made regarding their causality.

An acknowledged caveat to the inclusion of pathology data in multifactorial likelihood modeling is the underlying assumption that missense and in-frame deletions considered to be pathogenic mutations will exhibit the same tumor histopathological characteristics as do truncating mutations.

Since none of the approaches mentioned above have by itself been able to provide compelling evidence for or against pathogenicity of UVs, multifactorial likelihood models integrating these features have been developed [ 3, 4].

(17) Experimental approaches have also been complemented by studies using bioinformatics analysis based on multiple sequence alignment, 22) structure prediction, or multifactorial likelihood modeling in which available genetic data, co-occurrence, and predictive methods are combined.

On the other hand, two BRCA1 missense variants, c.5054C>T (p.Thr1685Ile) and c.5154G>T p.Trp1718Cyss), affecting highly conserved amino acid residues, have been predicted to be deleterious by a number of studies, including a multifactorial likelihood-ratio model [ 44], evolutionary conservation analyses and functional assays [ 39, 45, 46].

Maximum Likelihood (ML) analyses were performed using PALM (Phylogenetic Inference with Automatic Likelihood Model Selectors) [27].

We present our comparison of multifactorial likelihood predictions of pathogenicity and functional analysis of these BRCA1 variants.

EPS and likelihood model structure.