ATCC's Podcast: Behind the Biology

What does audio engineering have to do with gene editing? In this episode, David Yarmosh talks with Travis Hardcastle about the unexpected path that led him from music and sound production to CRISPR and product management. Travis shares how a move to Colorado helped launch his career in gene editing and reflects on how creativity, careful listening, and understanding people’s needs can shape success in both science and the arts. Together, they explore how curiosity and communication can turn unconventional experience into scientific impact.

In this episode of Behind the Biology, host David Yarmosh sits down with Travis Hardcastle to explore how gene editing connects scientific innovation, product development, and real customer needs. Travis breaks down the fundamentals of CRISPR, explains how automation supports the development of reliable gene-edited cell models, and highlights why quality control and transparent communication are essential for researchers working at the bench. The conversation also examines standardization, genetic drift, bioinformatics, and the growing need for trustworthy biological data as artificial intelligence becomes more integrated into life science research.

In this episode of Behind the Biology, David Yarmosh and Dr. Sanjeev Thohan explore how failure can become a powerful source of scientific knowledge. Sanjeev discusses the importance of separating the person from the experiment, examining what went wrong, and sharing unsuccessful results so others can learn from them. The conversation then turns to artificial intelligence and its potential to accelerate drug discovery by identifying patterns researchers might otherwise miss. Sanjeev also offers a grounded view of AI’s limitations, emphasizing that these tools are only as strong as the information they learn from—and that human creativity, experience, and judgment will remain essential to meaningful scientific progress.

What happens after the science works—but the path forward is still uncertain? In this episode, Dr. Sanjeev Thohan walks David Yarmosh through pivotal moments in malaria research, antiviral development, and biodefense that shaped his perspective on translating promising results into real-world impact. He discusses why strong data alone is not enough, highlighting the role of regulatory strategy, cross-functional teamwork, funding, and manufacturing in determining whether a program can advance. The episode also examines the leadership judgment required to know when to push ahead, when to pivot, and when to hand a promising effort to the team best positioned to carry it forward.

In this episode of Behind the Biology, David Yarmosh talks with Dr. Sanjeev Thohan about the curiosity, mentorship, and career experiences that shaped his approach to science and leadership. Sanjeev reflects on the value of asking both the obvious and overlooked questions, recognizing patterns across complex problems, and developing the situational awareness needed to move scientific programs forward. The conversation also explores the realities of startup leadership, including how difficult decisions, lessons from failure, and a willingness to challenge assumptions can help teams uncover opportunities others may miss.

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.