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3 results about "Processed Genes" patented technology

DNA vectors and elements for sustained gene expression in eukaryotic cells

ActiveUS12612646B2Sugar derivativesVectorsHeterologousProcessed Genes
The present invention provides polynucleotide vectors for high expression of heterologous genes. Some vectors further comprise novel elements that further improve expression. The gene transfer systems can be used in methods, for example, gene expression, bioprocessing, gene therapy, insertional mutagenesis, or gene discovery.
Owner:DNA TWOPOINTO INC

Transposition of nucleic acid constructs into eukaryotic genomes with a transposase from amyelois

The present invention provides polynucleotide vectors for high expression of heterologous genes. Some vectors further comprise novel transposons and transposases that further improve expression. Further disclosed are vectors that can be used in a gene transfer system for stably introducing nucleic acids into the DNA of a cell. The gene transfer systems can be used in methods, for example, gene expression, bioprocessing, gene therapy, insertional mutagenesis, or gene discovery.
Owner:DNA TWOPOINTO INC

Method for multiscale spatial transcriptomic domain identification based on block wavelet maps

PendingCN122347994AAlgorithmData information
The application discloses a multi-scale space transcriptome domain identification method based on a block wavelet graph, and comprises the following steps: acquiring original gene data of a space transcriptome; pre-processing the original gene data to obtain processed gene data; performing multi-scale feature extraction on the processed gene data to obtain feature data information; training a block-level model by using the feature data information to obtain a trained block-level model; outputting a block reasoning result by using the trained block-level model, and performing clustering analysis after global recombination of the block reasoning result to obtain a space domain division result. The application can accurately capture cross-scale biological signals, break through hardware limitations, and realize efficient and accurate space domain identification of super-large-scale µST data.
Owner:CHONGQING JIAOTONG UNIV