PATENT CLAIM ANALYSIS

Application Number: 15902948
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-12
Patent Classification: ["435", "006130"]

Abstract:
Described herein are methods of identifying compounds that can modulate the transport of a steroid hormone across a phospholipid membrane. Also described herein are methods of identifying compounds that can affect the transcriptional activity of a steroid hormone nuclear receptor.

Claim (Index 14):
A method of identifying a compound that can affect the transcriptional activity of a steroid hormone nuclear receptor, comprising:\n providing a steroid hormone to an initial cell and a comparative cell in either the presence or absence of a candidate compound, wherein the initial cell expresses a steroid hormone transporter gene, and the expression of the steroid hormone transporter gene in the comparative cell is absent or lower than in the initial cell; determining the transcriptional activity of the steroid hormone nuclear receptor in the initial cell and the comparative cell; observing a difference between the transcriptional activity in the initial cell in the presence of the candidate compound compared to the absence of the candidate compound; comparing the difference to the transcriptional activity of the comparative cell in the presence or absence of the candidate compound, and determining that the candidate compound can affect the transcriptional activity of a steroid hormone nuclear receptor if the amount of transcriptional activity is different in the initial cell than in the comparative cell, wherein the steroid hormone transporter gene is ecdysone importer (EcI).

Metadata:
- Claim Count in Document: 68.0
- Percentile: 88.0
- Lexical Diversity: 1.61538
- Patent Class: 435.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['11841644', '13615348', '15069057', '10468193', '12404943']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5743553045203365
- 35 USC 102 Novelty (BERT): 0.500742418899685
- Combined Prediction Score: 0.5669940159582713
- Mean Citation Score: 227.91041600000003
- Max Citation Score: 231.41635
- Similarity Product: 146.5958804983139

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