Beijing Baidu Netcom Science and Technology Co., Ltd.

Tsinghua University

Meng Tian

Xunchao Song

Wenbin Jiang

Xinwei Feng

Huanyu Zhou

Ying Li

Yong Zhu

Hongwei Wang

Pengcheng Yuan

Miao Yu

Yajuan Lyu

Jianbin Wang

Hongjian Shi

Xueqian Wu

Junlong Yin

The present invention provides a degradable microbead comprising a polymer molecule crosslinked by a crosslinking agent, wherein the polymer molecule and/or the crosslinking agent comprises a sensitive chemical bond that is cleavable through a chemical and/or light treatment, thereby resulting in the degradation of the degradable microbead. The present invention also provides a method of separating a target protein from a sample. By using the degradation of the degradable microbead to replace an elution step in protein purification, it is possible to select a combination of target protein and affinity ligand with a stronger affinity, thereby improving the protein purification efficiency. The method is especially suitable for the high-throughput preparation of multiple protein samples, for example providing a protein sample for electron microscope observation or mass spectrometry measurement.

Degradable microsphere and use thereof

The present disclosure discloses a question analysis method, a device, a knowledge base question answering system and an electronic equipment. The method includes: analyzing a question to obtain N linearized sequences, N being an integer greater than 1; converting the N linearized sequences into N network topology maps; separately calculating a semantic matching degree of each of the N network topology maps to the question; and selecting a network topology map having a highest semantic matching degree to the question as a query graph of the question from the N network topology maps. According to the technology of the present disclosure, the query graph of the question can be obtained more accurately, and the accuracy of the question to the query graph is improved, thereby improving the accuracy of question analysis.

Question analysis method, device, knowledge base question answering system and electronic equipment

The present disclosure discloses a method, apparatus, device, and storage medium for training a model, relates to the technical fields of knowledge graph, natural language processing, and deep learning. The method may include: acquiring a first annotation data set, the first annotation data set including sample data and a annotation classification result corresponding to the sample data; training a preset initial classification model based on the first annotation data set to obtain an intermediate model; performing prediction on the sample data in the first annotation data set using the intermediate model to obtain a prediction classification result corresponding to the sample data; generating a second annotation data set based on the sample data, the corresponding annotation classification result, and the corresponding prediction classification result; and training the intermediate model based on the second annotation data set to obtain a classification model.

Method, apparatus, device and storage medium for training model

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Beijing, China

Meng Tian