PATENT CLAIM ANALYSIS

Application Number: 16411045
Application Type: Utility
Filing Date: 2019-05
Publication Date: 2019-09
Patent Classification: ["435", "006120"]

Abstract:
Next Generation DNA sequencing promises to revolutionize clinical medicine and basic research. However, while this technology has the capacity to generate hundreds of billions of nucleotides of DNA sequence in a single experiment, the error rate of approximately 1% results in hundreds of millions of sequencing mistakes. These scattered errors can be tolerated in some applications but become extremely problematic when “deep sequencing” genetically heterogeneous mixtures, such as tumors or mixed microbial populations. To overcome limitations in sequencing accuracy, a method Duplex Consensus Sequencing (DCS) is provided. This approach greatly reduces errors by independently tagging and sequencing each of the two strands of a DNA duplex. As the two strands are complementary, true mutations are found at the same position in both strands. In contrast, PCR or sequencing errors will result in errors in only one strand. This method uniquely capitalizes on the redundant information stored in double-stranded DNA, thus overcoming technical limitations of prior methods utilizing data from only one of the two strands.

Claim (Index 53):
The method of  claim 37 , wherein the tags each comprise a barcode selected from about 2 to about 256 distinct barcode sequences.

Metadata:
- Claim Count in Document: 89.0
- Percentile: 100.0
- Lexical Diversity: 1.51639
- Patent Class: 435.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16411066', '16120019', '16120091', '15660785', '16120072']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.750889244025818
- 35 USC 102 Novelty (BERT): 0.6651289819040772
- Combined Prediction Score: 0.742313217813644
- Mean Citation Score: 711.6731560000003
- Max Citation Score: 766.6147
- Similarity Product: 612.9960845791936

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test