What question did this study set out to answer?

To develop and validate FATHMM, a hidden Markov model framework capable of predicting the functional and phenotypic impacts of nonsynonymous single nucleotide polymorphisms across diverse species.

October 3, 2012Human MutationOpen Access

Predicting the Functional, Molecular, and Phenotypic Consequences of Amino Acid Substitutions using Hidden Markov Models

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To develop and validate FATHMM, a hidden Markov model framework capable of predicting the functional and phenotypic impacts of nonsynonymous single nucleotide polymorphisms across diverse species.
Engineered FATHMM using hidden Markov models with species-independent architectures and species-specific weighting parameters.
Benchmarked the human-weighted model against existing prediction algorithms (SIFT, PolyPhen, PANTHER, SNPs&GO, and MutPred) across two benchmark datasets and applied it to wheat (Triticum spp.) sequencing data.
Human-weighted FATHMM outperformed traditional prediction tools SIFT, PolyPhen, and PANTHER across two independent benchmark datasets.
Achieved higher predictive accuracy than state-of-the-art predictors SNPs&GO and MutPred on one benchmark evaluation.
Successfully identified functional nonsynonymous variants linked to phenotypic shifts driven by artificial selection during wheat domestication.

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Implication

Computational evaluation demonstrates superior accuracy of hidden Markov models in predicting missense variant pathogenicity, highlighting their utility for high-throughput sequencing projects.

Cite This Study

Shihab et al. (2012) studied this question.

synapsesocial.com/papers/69f6916b7cfe3d0411fc8958 https://doi.org/10.1002/humu.22225

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Implication

Computational evaluation demonstrates superior accuracy of hidden Markov models in predicting missense variant pathogenicity, highlighting their utility for high-throughput sequencing projects.

Predicting the Functional, Molecular, and Phenotypic Consequences of Amino Acid Substitutions using Hidden Markov Models

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Discussion

Implication

Cite This Study

Predicting the Functional, Molecular, and Phenotypic Consequences of Amino Acid Substitutions using Hidden Markov Models

Key Points

Discussion

Implication

Cite This Study

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