Illumina had seven patents in big data during Q1 2024. Illumina Inc’s patents in Q1 2024 focus on improving base calling accuracy using neural networks, identifying duplicate fragments in sequencing data, classifying cancer conditions using genotypic data and convolutional neural networks, segmenting sequencing regions for sample contamination detection, and detecting infection-causing microbial DNA in biological samples based on size profiles and end signatures without the need for no template control samples. GlobalData’s report on Illumina gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Illumina grant share with big data as a theme is 14% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Artificial intelligence-based quality scoring (Patent ID: US20240071573A1)
The patent filed by Illumina Inc. describes a technology that assigns quality scores to bases called by a neural network-based base caller. This is achieved by quantizing classification scores of predicted base calls, determining base calling error rates, and correlating quality scores to the quantized classification scores. The system utilizes a neural network to identify base calls for analytes based on sequencing images, generate quality predictions for these base calls, and feed input data representing the sequencing images to the neural network. The system further includes instructions for feeding subsets of per-cycle image patches to the neural network, determining quality predictions by assigning quality scores, and classifying the quality of base calls as high, medium, or low quality based on likelihoods generated by the neural network.
Additionally, the system can generate quality predictions by assigning individual quality scores to base calls, utilizing a regression layer to identify continuous values representing the quality of base calls, and incorporating quality predictor values such as online overlap, purity, phasing, and peak characteristics. The technology also extends to a computer-implemented method that follows a similar process of identifying base calls, feeding input data to a neural network, generating quality predictions, and utilizing quality predictor values to enhance the accuracy of the predicted quality indications. Overall, the patent focuses on improving the accuracy and efficiency of base calling in sequencing processes through the use of neural networks and quality score assignments.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
