Manuel Jesus Reyes Gomez

Title: Innovations of Manuel Jesus Reyes Gomez

Introduction

Manuel Jesus Reyes Gomez is an accomplished inventor based in Kirkland, WA (US). He has made significant contributions to the field of predictive modeling, particularly in the context of protein-ligand interactions. With a total of 3 patents, his work has implications for advancements in biotechnology and computational biology.

Latest Patents

One of his latest patents is titled "Shift-invariant predictions." This patent describes a system for predicting binding information related to the interaction between a protein and a ligand. The system includes a trained binding model that features a hidden variable representing an unknown alignment of the ligand at the protein's binding site. The prediction component utilizes information about the sequences of both the protein and the ligand, along with the trained binding model, to predict binding information effectively.

Another notable patent is "Cluster modeling, and learning cluster specific parameters of an adaptive double threading model." This invention also focuses on predicting binding information between proteins and ligands. It includes a trained binding model that incorporates a probability distribution and hidden variables representing clusters of protein sequences. The prediction component is designed to leverage the sequences of the protein and ligand, along with the trained binding model, to enhance prediction accuracy.

Career Highlights

Manuel is currently employed at Microsoft Technology Licensing, LLC, where he continues to innovate and develop new technologies. His work at Microsoft has allowed him to collaborate with leading experts in the field, further enhancing his contributions to the scientific community.

Collaborations

Some of his notable coworkers include Nebojsa Jojic and David Earl Heckerman. Their collaborative efforts have likely contributed to the success of the projects they have worked on together.

Conclusion

Manuel Jesus Reyes Gomez is a prominent inventor whose work in predictive modeling has the potential to advance our understanding of protein-ligand interactions. His patents reflect a commitment to innovation and excellence in the field of biotechnology.