QIAGEN Biomedical KBs: Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Venkatesh Moktali, PhD, Director of Product Management, GPM – Digital Insights Base
Dmitrii Kamaev, Ph.D, Senior Product Owner
This talk will unveil QIAGEN’s Biomedical Knowledge Base products, elucidating their structure and schema design optimized for complex data exploration and sophisticated question-answering in the biomedical sector.
Key Takeaways:
Understanding the Structure: Gain insights into the structured design of the QIAGEN biomedical knowledge graphs, enhancing data scientists and bioinformaticians’ ability to navigate and utilize intricate datasets for drug development.
Schema Design: learn about the schema design tailored for exploration and question-answering, facilitating efficient data analysis and insight generation in biomedical research.
Integration with Large Language Models: Explore how these knowledge graphs are used in conjunction with large language models (LLMs) to revolutionize drug discovery applications, providing a cutting-edge approach to predictive analytics and decision-making.
Practical Applications: Deep dive into real-world applications, including link prediction models and their critical role in expediting drug discovery processes through advanced data analytics and machine learning techniques.