PATENT CLAIM ANALYSIS

Application Number: 16458376
Application Type: Utility
Filing Date: 2019-07
Publication Date: 2019-10
Patent Classification: ["702", "019000"]

Abstract:
The present disclosure provides a HTP microbial genomic engineering platform that is computationally driven and integrates molecular biology, automation, and advanced machine learning protocols. This integrative platform utilizes a suite of HTP molecular tool sets to create HTP genetic design libraries, which are derived from, inter alia, scientific insight and iterative pattern recognition. The HTP genomic engineering platform described herein is microbial strain host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any microbial host parameter of interest.

Claim (Index 11):
A method for engineering a host cell to have beneficial combinations of genetic alterations, comprising:\n a. populating a predictive machine learning model with a training data set, containing: i) at least one genetic alteration input variable representing at least one genetic alteration that has been introduced into a host cell, and ii) at least one measured phenotypic performance output variable representing at least one phenotypic performance measurement associated with the introduced genetic alteration; b. generating, in silico, a pool of design candidate host cells incorporating the at least one genetic alteration; c. utilizing the predictive machine learning model to predict the expected phenotypic performance of members of the pool of design candidate host cells that comprise a combination of genetic alterations selected from step (a) that are uncharacterized for improving phenotypic performance at the time of carrying out step (c); and d. manufacturing a member of the pool of design candidate host cells of step (c).

Metadata:
- Claim Count in Document: 17.0
- Percentile: 100.0
- Lexical Diversity: 1.45588
- Patent Class: 702.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15923527', '15396230', '15923555', '15923543', '16313613']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2955753686674387
- 35 USC 102 Novelty (BERT): 0.7205775582810537
- Combined Prediction Score: 0.3380755876288002
- Mean Citation Score: 604.2083819999998
- Max Citation Score: 794.4581
- Similarity Product: 711.0072157990694

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

Dataset: test