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Variant Analysis and AI for Discovery

Variant Analysis and AI for Discovery

“As the 20th anniversary of whole genome sequencing (WGS) via next-generation sequencing (NGS) approaches, it seems appropriate to review the bioinformatics challenges addressed, and those that lie ahead, […] where the application of AI seems most relevant.” – Dr. Scott Kahn

Today, the frontier has shifted. The toughest problems in bioinformatics lie downstream—interpreting variants, integrating complex datasets, and extracting clinically meaningful insights. This is where artificial intelligence and genetic analysis software are opening new possibilities for discovery and advancing precision medicine.

To explore these breakthroughs, Compass Bioinformatics Scientific Advisor, Dr. Scott Kahn, will lead a live webinar titled:

“Variant Analysis and AI for Discovery”

  • Date: Friday, August 22, 2025
  • Time: 3pm EST | 2pm CST | 1pm MST | 12pm PST
  • 🔗 Register Here

The goal of this webinar is to suggest a few interesting opportunities for bioinformatics professionals to tackle to improve our understanding of human health and disease.

Hosted by our alliance partner, the MidSouth Computational Biology and Bioinformatics Society (MCBIOS), this session will dive into how AI is reshaping genomics data analysis, from variant interpretation to translational applications in human health and disease.


About Our Partner:

The MidSouth Computational Biology and Bioinformatics Society (MCBIOS) advances the fields of bioinformatics and computational biology by:

  • Connecting scientists from diverse backgrounds and disciplines
  • Facilitating collaboration to solve complex biological, health, and medical problems
  • Promoting education in bioinformatics and genomics research
  • Informing the public on the results and implications of current research
  • Supporting and mentoring trainees in the field

Through events like this webinar, MCBIOS continues its mission to connect researchers, inspire innovation, and support the next generation of leaders in computational biology.

For more info, visit: https://mcbios.com/

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