7 results about "Homology analysis" patented technology

This invention provides a method for mining tumor antigens derived from endogenous retroviruses. The method involves bulk RNA-seq sequencing of tumor tissue and adjacent normal tissue samples using a splicing strategy to obtain DNA sequences of human endogenous retrovirus (HERV)-derived transcripts (hervRNA). Subsequently, a specific screening strategy is employed to obtain candidate open reading frames (ORF) sequences on tumor-specific hervRNAs. Finally, homology analysis, prediction of binding energy to human leukocyte antigen class I (HLA-I) molecules, and multi-site analysis are used to predict and mine neoantigens derived from HERV in tumors.

This invention discloses a method for constructing a Brca2-p.Q462Ter genetically engineered mouse and its application. The Brca2 genetically engineered mouse provided by this invention carries a truncated mutation in its Brca2 gene. This mutation is located at exon 10 of the mouse Brca2-201 transcript, changing amino acid position 462 from glutamine Q (Gln) to the stop codon Ter, forming the Brca2-p.Q462Ter mutation. The Brca2-p.Q462Ter genetically engineered mouse is used to simulate the human BRCA2 gene truncated mutation p.Gln472Ter, c.1414C>T. Amino acid homology analysis shows that the mouse BRCA2 protein Q462 site is homologous to the human BRCA2 protein Q472 site; therefore, this mouse mutation site can be used to simulate the corresponding truncated mutation effect in human BRCA2. This genetically engineered mouse can simulate, at the whole animal level, the abnormal DNA damage repair, impaired homologous recombination repair function, decreased genome stability, and susceptibility to related diseases caused by BRCA2 truncated mutations, thus providing a reliable tool for research on BRCA2-related pathogenesis, developmental effects, drug screening, and efficacy evaluation.

The present application relates to a kind of biological species homology analysis systems based on protein / gene sequence data, belong to biological species homology analysis technical field, solve the problem of high cost and low efficiency of detection method in prior art.The system of the present application includes: data preprocessing module, for the obtained protein / gene original data is carried out data cleaning, obtain protein / gene sequence data;Data analysis module includes: protein sequence analysis unit, for according to the frequency of each amino acid in protein sequence, position and its physical and chemical properties, generate protein sequence numerical representation vector;Gene sequence analysis unit, for obtaining the optimal matching sequence in two groups of gene sequences;Species homology judging module, for according to protein sequence numerical representation vector / optimal matching sequence, the distance of each two groups of protein / gene sequence data is calculated, and according to the size of distance, the analysis of protein / gene sequence homology nearness.

The application provides an attack homologous analysis method, system, electronic equipment and storage medium, and relates to the technical field of network security. The method comprises the following steps: obtaining event clues, alarm data and sample data of a to-be-tested attack event; extracting ATT&CK tactics and technology features from the alarm data, extracting sample HASH values and code features from the sample data, and extracting attack industry and country features from the event clues; respectively calculating the similarity between the extracted features and corresponding features in a preset APT organization feature library; calculating a comprehensive similarity score based on each similarity, and determining the homologous APT organization of the to-be-tested attack event according to the comprehensive similarity score. The application integrates multiple-dimensional data sources, breaks through the analysis blind area caused by a single data source, simultaneously fuses static code and dynamic alarm features, effectively overcomes the false alarm problem caused by incomplete confusion code disassembly, and significantly improves the accuracy, comprehensiveness and robustness of attack tracing and homologous identification.

This invention discloses an event aggregation and attribution method based on attack chain homology analysis, comprising the following steps: Step 1, multi-source heterogeneous data fusion and standardization processing; Step 2, dynamic subject-object relationship modeling; Step 3, attack event homology analysis; Step 4, homology attack event aggregation; Step 5, attack path deduction and visualization; Step 6, dynamic threat adaptive optimization. This invention improves the completeness of attack path reconstruction and solves the defect of static modeling in failing to capture attack chain evolution by using a dynamic subject-object relationship model and homology analysis algorithm; it presents the attack process through visualization technology, shortening the analysis time and improving the efficiency of source tracing; it improves the robustness of homology determination and the accuracy of entity relationship identification by using a multi-feature weighted fusion hierarchical clustering mechanism combined with code string features and vulnerability exploitation methods for auxiliary verification; and it enhances the adaptability of dynamic threats and shortens the response window for new threats through a dynamic weight update mechanism.

Embodiments of the present application provide a method and device for homologous analysis of an Internet Protocol address, and a storage medium. The method comprises: obtaining an Internet Protocol address to be analyzed and corresponding original features; obtaining a plurality of reference Internet Protocol addresses and reference features corresponding to each reference Internet Protocol address; establishing a heterogeneous information graph structure based on associated sub-features between the original features and each reference feature; inputting the heterogeneous information graph structure into a target model; updating the original features of a target node based on the reference features associated with each reference node, the associated sub-features between the reference features and the original features associated with the target node, and the associated weights of the connection edges between each reference node and the target node, to obtain target features; and outputting a homologous analysis result corresponding to the Internet Protocol address to be analyzed based on the target features by the target model. In this way, the accuracy of homologous analysis of the Internet Protocol address can be improved.