5 results about "Sequence comparison" patented technology

The application belongs to the field of molecular biology identification, and particularly relates to a specific SNP site combination for identifying Duntou pig breeds and application. The specific SNP site combination for identifying Duntou pig breeds comprises 40 SNP sites, and the physical position is based on the reference genome of pigs Sscrofa11.1 The sequence comparison is determined. The specific SNP site combination is screened based on the method of whole genome association analysis combined with selection signal analysis, so as to ensure the accuracy of site selection. The specific SNP site combination provided by the application can rapidly realize the accurate identification of Duntou pig breeds at the gene level, and has significant application value in the accurate protection of Hainan local pig genetic resources and breed utilization.

This invention discloses a method for specifically recognizing antigen epitopes. 16 AQTGYAPV 23 This invention relates to a monoclonal antibody D3-mAb against porcine rotavirus and its applications, belonging to the field of antibody bioengineering technology. The monoclonal antibody D3-mAb specifically binds to the VP8 protein of porcine rotavirus and exhibits neutralizing activity; its amino acid sequence is shown in SEQ ID NO. 8. This invention screened a monoclonal antibody D3 with neutralizing activity against the VP8 protein, and subsequently identified the neutralizing antigenic epitope. 16 AQTGYAPV 23 Recognized by D3-mAb, sequence comparison analysis of currently circulating PoRVA strains revealed that this antigenic epitope is absolutely conserved. Furthermore... 16 AQTGYAPV 23 The epitope, located on the surface of the VP8 protein, interacts with the antibody's variable region via six hydrogen bonds. This invention provides a novel approach for designing novel epitope vaccines and antiviral strategies, and the provided monoclonal antibody holds promise for development into a biotherapeutic agent and diagnostic agent for porcine rotavirus infection.

The application provides a protein-metal ion binding site recognition method, device and equipment, and belongs to the field of protein detection. The method comprises the following steps: extracting features of known metal ion binding proteins to obtain a plurality of sample evolutionary information features; for an unknown protein sequence, candidate distant homologous metal ion binding proteins are determined through multiple sequence comparison and cosine similarity screening, and a training set is constructed; a composite framework of a bidirectional long short-term memory network and a full connection neural network is adopted, input features include evolutionary information features and physicochemical property features, and output is probability values of different metal ion binding sites; the composite framework is trained through the training set to obtain a site prediction model; and the prediction model is used to predict the binding sites of the unknown protein sequence. Stable and efficient prediction of metal ion binding sites is realized.

The application discloses antibody preparation capable of detecting various IMP variants and application thereof, and belongs to the field of biological medicine. According to the amino acid sequence comparison of various IMP variants, a conserved antigen epitope sequence of IMP enzyme is obtained, and an antibody of the spatial antigen epitope is prepared through structure analysis of the antigen epitope. After mice are immunized with IMP immunogen proteins, hybridoma cells secreting antibodies are obtained through multi-technology platform screening, specific antibodies MK35G9 and MK56G2 with high affinity and capable of combining various IMP variants are obtained through sequencing, and corresponding CDRs are analyzed and obtained. The application is based on an immunochromatography platform to develop an IMP enzyme detection product, and has the advantages of high sensitivity, good specificity, covering various IMP variants, rapid and convenient detection, and the like, and provides important help for clinical auxiliary diagnosis and medication guidance.

This application provides a method, apparatus, and device for training a neural network model to determine mutation sites. The method includes: detecting candidate mutation sites in a sequence comparison file generated by comparing the sequencing sequence of a preset tumor sample with a preset reference genome, and adding artificial labels; encoding the candidate mutation sites into multi-channel image tensors based on the alignment information of the sequence comparison file, wherein each channel records a feature; selecting a first preset number of reads from each candidate mutation site and its upstream and downstream regions according to a preset screening rule, and merging them with a second preset number of reference sequences to form a mutation feature set for feature processing; generating image-label pairs as a sample set based on the mutation feature set and the artificial labels of the mutation sites; training a neural network model based on a training set and a validation set obtained from the sample set, and performing hyperparameter tuning using the validation set.