Noah Aaron Zaitlen

Title: The Innovative Contributions of Noah Aaron Zaitlen

Introduction

Noah Aaron Zaitlen is a notable inventor based in Venice, CA. He has made significant contributions to the field of predictive modeling, particularly in the context of protein interactions and epitope predictions. With a total of 2 patents, Zaitlen's work is recognized for its potential impact on biotechnology and medicine.

Latest Patents

Zaitlen's latest patents include "Shift-invariant predictions" and "T-cell epitope prediction." The first patent describes a system for predicting binding information related to the interaction between a protein and a ligand. This system utilizes a trained binding model that incorporates a hidden variable to represent the unknown alignment of the ligand at the protein's binding site. The prediction component is designed to utilize information from both the protein's and ligand's sequences to enhance the accuracy of binding predictions.

The second patent focuses on epitope prediction models. It outlines a system that employs a classification model, such as a logistic regression model, to predict epitope information. This model processes protein data and incorporates hidden binary variables and shift variables to identify desired epitopes. The classification model is adept at predicting epitope information by analyzing various features related to epitopes and MHC (Major Histocompatibility Complex).

Career Highlights

Noah Zaitlen is currently associated with Microsoft Technology Licensing, LLC, where he continues to innovate and develop new technologies. His work at Microsoft has allowed him to explore advanced predictive modeling techniques that have applications in various scientific fields.

Collaborations

Zaitlen has collaborated with notable colleagues, including Nebojsa Jojic and David Earl Heckerman. These collaborations have contributed to the advancement of his research and the development of his patented technologies.

Conclusion

Noah Aaron Zaitlen's contributions to predictive modeling in biotechnology are noteworthy. His innovative patents reflect a deep understanding of protein interactions and epitope predictions, showcasing his role as a leading inventor in this field.