PATENT CLAIM ANALYSIS

Application Number: 16001569
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2019-02
Patent Classification: ["702", "019000"]

Abstract:
Disclosed herein is a system and methods for determining the alleles, neoantigens, and vaccine composition as determined on the basis of an individual's tumor mutations. Also disclosed are systems and methods for obtaining high quality sequencing data from a tumor. Further, described herein are systems and methods for identifying somatic changes in polymorphic genome data. Finally, described herein are unique cancer vaccines.

Claim (Index 5):
The method of  claim 1 , wherein inputting the numerical vector into the machine-learned presentation model comprises:\n applying the machine-learned presentation model to the peptide sequence of the neoantigen to generate a dependency score for each of the one or more class I MHC alleles indicating whether the class I MHC allele will present the neoantigen based on the particular amino acids at the particular positions of the peptide sequence.

Metadata:
- Claim Count in Document: 71.0
- Percentile: 94.0
- Lexical Diversity: 1.47917
- Patent Class: 702.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15466729', '15210489', '15170919', '15791301', '13640989']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2376711043550485
- 35 USC 102 Novelty (BERT): 0.6752803382276378
- Combined Prediction Score: 0.2814320277423074
- Mean Citation Score: 382.58593
- Max Citation Score: 726.4492
- Similarity Product: 654.3597118283749

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

Dataset: test