Christopher Harron Woelk

Title: Christopher Harron Woelk: Innovator in Biosynthetic Gene Clusters

Introduction

Christopher Harron Woelk is a notable inventor based in Winchester, MA (US). He has made significant contributions to the field of biosynthetic gene clusters through his innovative patent. His work focuses on utilizing machine learning to identify candidate biosynthetic gene clusters within genomes.

Latest Patents

Woelk holds a patent for a system that identifies biosynthetic gene clusters (BGCs) using machine-learned models, including a shallow neural network and a recurrent neural network (RNN). This system identifies domains within a genome sequence, with each domain corresponding to a set of domain identifiers. A shallow neural network block processes these identifiers to produce vectors, while an RNN block generates a BGC class score for each domain. The RNN block is trained using both positive vectors, representing known BGCs, and synthesized negative vectors, which are unlikely to represent BGCs. Candidate BGCs are selected by averaging BGC class scores across genes within a domain and comparing these averages to a threshold. The resulting candidate BGCs are then displayed on a user interface.

Career Highlights

Throughout his career, Woelk has worked with prominent companies, including Merck Sharp & Dohme Corporation and MSD Czech Republic S.r.o. His experience in these organizations has contributed to his expertise in the field of biosynthetic research and development.

Collaborations

Woelk has collaborated with notable professionals in his field, including Geoffrey D. Hannigan and David Prihoda. These collaborations have likely enhanced his research and innovation efforts.

Conclusion

Christopher Harron Woelk is a distinguished inventor whose work in identifying biosynthetic gene clusters has the potential to advance the field of genomics significantly. His innovative approach using machine learning exemplifies the intersection of technology and biological research.