ATCC's Podcast: Behind the Biology

In this episode, Dr. Ryan Wick explores the technologies and ideas that are shaping the future of microbial genomics. Dr. Wick discusses how advances in machine learning have dramatically improved the accuracy of next-generation sequencing, helping scientists translate complex electrical signals into reliable DNA sequences. He explains the differences between traditional computational approaches and modern AI-driven methods, highlighting how improvements in algorithms and biochemistry have worked together to advance long-read sequencing. Looking ahead, Dr. Wick shares his perspective on emerging opportunities in metagenomics, eukaryotic genome assembly, and the continued evolution of tools designed to make genomic analysis more accurate and accessible.

In this episode, Dr. Ryan Wick discusses the path that led him into bioinformatics and the technologies that have shaped his work in bacterial genomics. Dr. Wick shares how an early interest in biology evolved through careers in healthcare software and science education into a passion for programming and computational biology. He explains how that journey led to the development of a tool that helps scientists visualize genome assembly graphs, and later a hybrid assembler that combines short- and long-read sequencing data to create complete bacterial genome assemblies. Dr. Wick also explores how advances in next-generation sequencing, machine learning, and bioinformatics algorithms have improved the accuracy and accessibility of genome assembly.

In this episode, Dr. Ryan Wick to explore the tools and ideas that have shaped modern bacterial genome assembly. Dr. Wick explains how his bioinformatics tools used for bacterial genome assembly help scientists turn sequencing reads into complete, usable genomes. He breaks down the unique challenges of genome assembly and why bacterial isolates are especially well suited to hybrid approaches that combine short- and long-read data. Throughout the conversation, Dr. Wick emphasizes the importance of choosing the right tool for the right scientific question, noting that every assembly method has strengths, limitations, and intended use cases.

Tune in, to hear Dr. Scott Nguyen explore what it means to trust scientific data while still questioning it carefully. Dr. Nguyen shares a memorable comparison between bioinformatics and storm chasing. In both cases, he explains, you look at data, interpret clues, make predictions, and understand that the information may not be perfect. For storm chasing, that might mean comparing radar images with what you can see in the sky. In genomics, it means checking sequencing results with other tools, understanding how the experiment was run, and making sure the conclusions are supported. The conversation also touches on imposter syndrome and how learning to trust the scientific process can help build confidence. Dr. Nguyen’s storm-chasing example is connected back to his work with genomic data, showing how curiosity, caution, and experience all play a role in good science.

Listen in, as Dr. Scott Nguyen continues the conversation by looking at how sequencing data becomes something scientists can actually use. Dr. Nguyen explains that biological data should not be interpreted on its own. To understand what a genome sequence really means, scientists need to consider where the sample came from, how the experiment was performed, what tools were used, and what limitations may exist. He then shapes the discussion around the bigger picture: bioinformatics is not just about running data through software — it also requires judgment, context, and careful review.