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NEURAL NETWORK ARCHITECTURES FOR SCORING AND VISUALIZING BIOLOGICAL SEQUENCE VARIATIONS USING MOLECULAR PHENOTYPE, AND SYSTEMS AND METHODS THEREFOR
NEURAL NETWORK ARCHITECTURES FOR SCORING AND VISUALIZING BIOLOGICAL SEQUENCE VARIATIONS USING MOLECULAR PHENOTYPE, AND SYSTEMS AND METHODS THEREFOR
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机译:使用分子表型对生物序列变异进行评分和可视化的神经网络体系结构,系统和方法
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摘要
Systems and methods for scoring and visualizing the effects of variants in biological sequences. Variants may include substitutions, insertions and deletions. The method comprises encoding biological sequences as vector sequences and then operating a neural network in the forward-propagation mode and possibly in the back-propagation mode to compute variant scores. Variant scores are determined by normalizing the gradients. Variant scores may be used to select a subset of variants, which are then used to produce modified vector sequences which are analyzed by the neural network operating in forward-propagation mode, to determine improved variant scores. The variant scores may be visualized using black and white, greyscale or colored elements that are arranged in blocks with dimensions corresponding to different possible symbols and the length of the sequence. These blocks are aligned with the biological sequence, which is illustrated by a symbol sequence arranged in a line.
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