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March 23, 2026BioinformaticsOpen Access

NCBoost v2: a classifier for non-coding single nucleotide variants in Mendelian diseases

Barthélémy Caron Antonio Rausell

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Key Points

To develop NCBoost v2, a classifier targeted at identifying non-coding single nucleotide variants associated with Mendelian diseases.
Developed a classification algorithm based on genetic data.
Focused on non-coding regions of the genome.
Utilized bioinformatics tools for data analysis.
NCBoost v2 shows improved accuracy in classifying variants compared to previous models.
Effectiveness noted for a variety of Mendelian disease contexts.

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Implication

Bioinformatics tool classifies non-coding single nucleotide variants in Mendelian diseases, indicating its potential for genetic analysis.

Abstract

Supplementary data are available at Bioinformatics online.

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Cite This Study

Caron et al. (2026) studied this question.

synapsesocial.com/papers/69c7722a8bbfbc51511e27b6 https://doi.org/10.1093/bioinformatics/btag138

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Keep reading

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1NCBoost v2: a classifier for non-coding variants in Mendelian diseases2025 · 1 citations
2Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditionsother · 2020 · 2 citations
3Evaluation of BoostDM, a somatic variant prediction tool, for the interpretation of germline variants in hereditary cancer genesReview · 2026 · 1 citations
4Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditionsother · 2020 · 63 citations
5Estimation of pleiotropy between complex diseases using single-nucleotide polymorphism-derived genomic relationships and restricted maximum likelihoodGWAS · 2012 · 631 citations

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