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Development of pathogenicity predictors specific for variants that do not comply with clinical guidelines for the use of computational evidence

机译:针对不符合使用计算证据的临床指南的变体的致病性预测因子的开发

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摘要

BackgroundStrict guidelines delimit the use of computational information in the clinical setting, due to the still moderate accuracy of in silico tools. These guidelines indicate that several tools should always be used and that full coincidence between them is required if we want to consider their results as supporting evidence in medical decision processes. Application of this simple rule certainly decreases the error rate of in silico pathogenicity assignments. However, when predictors disagree this rule results in the rejection of potentially valuable information for a number of variants. In this work, we focus on these variants of the protein sequence and develop specific predictors to help improve the success rate of their annotation.
机译:背景技术由于计算机工具的准确性仍然中等,因此严格的准则限制了在临床环境中使用计算信息。这些准则表明,应始终使用几种工具,并且如果我们希望将其结果视为医疗决策过程中的支持证据,则需要它们之间完全一致。应用此简单规则肯定会降低计算机病原学分配的错误率。但是,当预测变量不同意时,此规则将导致许多变体的潜在有价值信息被拒绝。在这项工作中,我们专注于蛋白质序列的这些变异,并开发出特定的预测因子,以帮助提高其注释的成功率。

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