Prediction method and device, electronic equipment and storage medium

A prediction method and material technology, applied in the computer field, can solve the problems of low efficiency of manual experiments and low accuracy of prediction results, and achieve the effects of improving extraction efficiency and accuracy, improving accuracy, and improving prediction efficiency

Pending Publication Date: 2021-10-01
SHANGHAI SENSETIME INTELLIGENT TECH CO LTD
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the efficiency of manual experiments is low, and the accuracy of prediction results obtained by traditional statistical methods is low

Method used

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  • Prediction method and device, electronic equipment and storage medium
  • Prediction method and device, electronic equipment and storage medium
  • Prediction method and device, electronic equipment and storage medium

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Embodiment Construction

[0025] Various exemplary embodiments, features, and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numbers in the figures indicate functionally identical or similar elements. While various aspects of the embodiments are shown in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

[0026] The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration." Any embodiment described herein as "exemplary" is not necessarily to be construed as superior or better than other embodiments.

[0027] The term "and / or" in this article is just an association relationship describing associated objects, which means that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist simultaneously, and there exists alone B these three situations. In addition, the term "at least one" herein mean...

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Abstract

The invention relates to a prediction method and device, electronic equipment and a storage medium. The method comprises the steps: carrying out the feature extraction of the molecular structure data of a to-be-detected substance through a drug feature extraction network, and obtaining a molecular feature, wherein the drug feature extraction network is any one of a full-connection neural network, a convolutional neural network or a sequence-based neural network; performing feature extraction on the gene data of the target object through a gene feature extraction network to obtain gene features; fusing the molecular features and the gene features to obtain fused features; and predicting a reaction result between the to-be-detected substance and the target object according to the fused features. According to the embodiment of the invention, when the reaction result between the drug and the gene is predicted, feature extraction is carried out through the neural network, so that the processing efficiency can be improved, and the prediction accuracy can be improved.

Description

technical field [0001] The present disclosure relates to the field of computer technology, and in particular to a prediction method and device, electronic equipment, and a storage medium. Background technique [0002] Gene drug response is a study that combines gene function and molecular pharmacology. In related technologies, the response of genes to drugs is usually quantitatively analyzed through manual experiments, or the relationship between genes and drugs is predicted by using traditional statistical methods such as matrix decomposition based on the similarity of genes. However, the efficiency of manual experiments is low, and the accuracy of prediction results obtained by traditional statistical methods is low. Contents of the invention [0003] The present disclosure proposes a prediction technical solution. [0004] According to one aspect of the present disclosure, a prediction method is provided, including: performing feature extraction on the molecular struc...

Claims

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Application Information

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IPC IPC(8): G16B15/00G16B20/50G16B25/10G16C20/50G06N3/04G06N3/08
CPCG16B15/00G16B20/50G16B25/10G16C20/50G06N3/08G06N3/045
Inventor 黎瑛张捷
Owner SHANGHAI SENSETIME INTELLIGENT TECH CO LTD
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