ATCC's Podcast: Behind the Biology

ATCC: Behind the Biology Podcast

ATCC's Podcast: Behind the Biology is a science podcast hosted by ATCC, with 49 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

ATCC hosts ATCC's Podcast: Behind the Biology, a science show with 49 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  Episode #52

  Episode 52: From Signals to Sequences

  Aug 18, 202628 minS4

  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.

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  Episode #51

  Episode 51: What Storm Chasers Can Teach Data Scientists

  Aug 11, 202626 minS4

  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.

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  Episode #50

  Episode 50: Every Genome Has a Story

  Aug 4, 202627 minS4

  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.

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  Episode #49

  Episode 49: Without Context, Data Lies

  Jul 28, 202629 minS4

  In this episode, Dave Yarmosh sits down with Dr. Scott Nguyen to introduce the world of biocuration and why it matters in modern biology. Dr. Nguyen explains that biocuration is all about making sure scientific data is connected to the right information. In sequencing work, that means confirming that a genome is matched to the correct strain and that the strain’s background details, or metadata, are accurate. He breaks down why this matters: even the best sequencing data can become confusing or misleading if it is not connected to the right biological context. Dr. Nguyen closes by discussing how scientists need a clear starting point for understanding how careful data organization supports trustworthy science.

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  Episode #48

  Episode 48: Innovation to Application- The Next Chapter of Microphysiological Systems

  Jun 9, 202618 minS3

  <p>What’s next for microphysiological systems? In this episode, Dr. Carolina Lucchesi shares her perspective on how these technologies are advancing toward broader adoption in research and drug development. She discusses the potential of patient-derived models to support personalized medicine, the integration of experimental and in silico approaches, and the hurdles that remain in scaling and automation. The conversation also examines the role of MPS in improving safety and predictability—from early drug screening to infectious disease research—while offering a realistic outlook on their future impact.</p>

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