In Silico Systems Biology Analysis of Variants of Uncertain Significance in Lynch Syndrome Supports the Prioritization of Functional Molecular Validation.

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In Silico Systems Biology Analysis of Variants of Uncertain Significance in Lynch Syndrome Supports the Prioritization of Functional Molecular Validation.

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2017 nî lūn-bûn

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2017年の論文

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2017年学术文章

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2017年学术文章

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2017年学术文章

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2017年学术文章

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2017年学术文章

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2017年學術文章

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In Silico Systems Biology Anal ...... nctional Molecular Validation.

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In Silico Systems Biology Anal ...... nctional Molecular Validation.

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In Silico Systems Biology Anal ...... nctional Molecular Validation.

@en

In Silico Systems Biology Anal ...... nctional Molecular Validation.

@nl

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In Silico Systems Biology Anal ...... nctional Molecular Validation.

@en

In Silico Systems Biology Anal ...... nctional Molecular Validation.

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P1476

In Silico Systems Biology Anal ...... unctional Molecular Validation

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P2093

Amanda Cuddy

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Eduardo Vilar

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Ester Borras

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Jennifer L Bosch

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Mala Pande

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Maureen E Mork

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Melissa W Taggart

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Miguel A Rodriguez-Bigas

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Patrick M Lynch

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Sarah A Bannon

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P2860

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Prediction and assessment of splicing alterations: implications for clinical testing.

A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data.

Tumor characteristics as an analytic tool for classifying genetic variants of uncertain clinical significance.

Current clinical criteria for Lynch syndrome are not sensitive enough to identify MSH6 mutation carriers.

Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.

In silico prediction of splice-altering single nucleotide variants in the human genome.

P304

580-587

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scholarly article

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10.1158/1940-6207.CAPR-17-0058

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P433

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P478

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Kyle Chang

P577

2017-08-01T00:00:00Z

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28765196

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5626617

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