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SYSTEMS AND METHODS FOR CLASSIFYING, PRIORITIZING AND INTERPRETING GENETIC VARIANTS AND THERAPIES USING A DEEP NEURAL NETWORK

机译:使用深层神经网络对遗传变量和治疗进行分类,定级和解释的系统和方法

摘要

Described herein are systems and methods that receive as input a DNA or RNA sequence, extract features, and apply layers of processing units to compute one ore more condition-specific cell variables, corresponding to cellular quantities measured under different conditions. The system may be applied to a sequence containing a genetic variant, and also to a corresponding reference sequence to determine how much the condition-specific cell variables change because of the variant. The change in the condition-specific cell variables are used to compute a score for how deleterious a variant is, to classify a variant's level of deleteriousness, to prioritize variants for subsequent processing, and to compare a test variant to variants of known deleteriousness. By modifying the variant or the extracted features so as to incorporate the effects of DNA editing, oligonucleotide therapy, DNA- or RNA-binding protein therapy or other therapies, the system may be used to determine if the deleterious effects of the original variant can be reduced.
机译:在此描述的系统和方法接收输入的DNA或RNA序列,提取特征并应用处理单元层以计算一个或多个条件特定的细胞变量,这些变量对应于在不同条件下测得的细胞数量。该系统可以应用于包含遗传变异体的序列,并且还可以应用于相应的参考序列,以确定条件特异性细胞变量由于变异而改变了多少。特定条件单元格变量的变化用于计算变体的有害程度得分,分类变体的有害程度,为变体确定优先级以进行后续处理,以及将测试变体与已知有害性的变体进行比较。通过修改变体或提取的特征,以便结合DNA编辑,寡核苷酸治疗,DNA或RNA结合蛋白治疗或其他疗法的作用,该系统可用于确定原始变体的有害作用是否可以减少。

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