Little Rock, AR, United States of America

Jackson O Lay, Jr


Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 23(Granted Patents)


Company Filing History:


Years Active: 2005

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1 patent (USPTO):Explore Patents

Title: Jackson O Lay, Jr: Innovator in Spectral Data Analysis

Introduction

Jackson O Lay, Jr. is a notable inventor based in Little Rock, AR (US). He has made significant contributions to the field of molecular analysis through his innovative patent. His work focuses on predicting the biological, chemical, and physical properties of molecules using their spectral properties.

Latest Patents

Jackson O Lay, Jr. holds a patent titled "Methods for predicting the biological, chemical, and physical properties of molecules from their spectral properties." This patent discloses methods for establishing a quantitative relationship between the spectral properties of molecules and their biological, chemical, or physical endpoints. The methods utilize spectral data from various techniques, including nuclear magnetic resonance, mass spectrometry, infrared, and ultraviolet-visible spectroscopy. The training of a pattern-recognition program yields a spectral data-activity relationship that can predict the endpoint value of a molecule based solely on its spectral data. Additionally, the patent includes methods for rapidly screening isolated compounds or mixtures based on their spectral data.

Career Highlights

Jackson O Lay, Jr. is affiliated with the National Institutes of Health, a component of the US Department of Health & Human Services. His work at this esteemed institution has allowed him to contribute to advancements in molecular analysis and predictive modeling.

Collaborations

Some of his notable coworkers include Dwight Wayne Miller and Richard D Beger. Their collaborative efforts have further enhanced the research and development in the field of spectral data analysis.

Conclusion

Jackson O Lay, Jr. is a distinguished inventor whose work in predicting molecular properties through spectral data has significant implications in various scientific fields. His contributions continue to influence research and innovation in molecular analysis.

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