MACHINE LEARNING APPLICATIONS TO PREDICT BIOLOGICAL OUTCOMES AND ELUCIDATE UNDERLYING BIOLOGICAL MECHANISMS

Abstract: systems and methods for modeling highly complex biological relations in machine-learned models, such as neural networks (e.g., such as deep neural networks (dnns)), to predict biological outcomes and elucidate underlying mechanisms are described. the systems and methods utilize recursive feature elimination and scoring and can be utilized to prioritize particular compounds or treatments for clinical development and direct new avenues of research and development based on elucidated mechanisms.

Inventor(s): Taranjit Gujral, Siddharth Vijay

CPC Classification: G16B5/00 (ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks)

Search for rejections for patent application number 20250166723