PATENT CLAIM ANALYSIS

Application Number: 15952962
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2018-10
Patent Classification: ["435", "006100"]

Abstract:
Embodiments in accordance with the present disclosure are directed to assessing for the presence of different target sequences in a sample. Embodiments include providing a binary result of the presence or absence of target sequences that is indicative of a disease or other physiological condition. An example method includes exposing a sample to a plurality of probes, the plurality of probes including a plurality of complimentary sequences that bind to a plurality of target sequences in the sample, and a plurality of different tag sequences for each of the plurality of target sequences in the sample. At least a portion of the target sequences bound to the probes are caused to bind to the different locations on the substrate. And, the method includes, by using scanning circuitry and information indicative of the different locations and associated tag sequences, assessing the number of the target sequences in the sample.

Claim (Index 18):
The apparatus of  claim 10 , wherein the plurality of complementary tag sequences are arranged at the plurality of different locations on the substrate, each location being unique to one of the plurality of probes configured and arranged to bind to the respective complementary tag sequences.

Metadata:
- Claim Count in Document: 26.0
- Percentile: 91.0
- Lexical Diversity: 2.50794
- Patent Class: 435.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['13327526', '09616787', '11829861', '11036833', '13239585']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5697884624014895
- 35 USC 102 Novelty (BERT): 0.5080442506981403
- Combined Prediction Score: 0.5636140412311546
- Mean Citation Score: 226.819832
- Max Citation Score: 234.37436
- Similarity Product: 153.38276538601875

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

Dataset: test