Featuring Dr. Ryan Wick
Show Notes:
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.
Guest:
Ryan Wick, PhD
Postdoctoral Researcher, Center for Pathogen Genomics, University of Melbourne
Ryan Wick is a postdoctoral researcher at the University of Melbourne's Center for Pathogen Genomics where he works on assembly algorithms for bacterial genomes. He has a particular interest in long-read assembly and hybrid assembly which combines both short and long reads. Additionally, Dr Wick is the developer of digital bioinformatic tools such as Bandage, Unicycler, Porechop, Filtlong, Badread, Trycycler, Polypolish and Autocycler. Dr. Wick earned a Bachelors from the University of Wisconsin, a Master of Science at the University of Melbourne, and Doctor of Philosophy under Dr. Kathryn Holt at the University of Monash.
Host:
David Yarmosh, MS
Lead Bioinformatician, ATCC
David Yarmosh is a lead bioinformatician in ATCC’s Sequencing and Bioinformatics Center. He’s a graduate of New York University’s Tandon School of Engineering. He has been working in large data aggregation and analysis since 2013 and microbial genomics with a focus on biosurveillance R&D efforts since 2016. David has led international training exercises in Peru and Senegal, sharing metagenomic analytical capabilities. His interests include genomics database construction, metadata collection, drug resistance mechanisms, bioinformatics standards, and machine learning. Since joining ATCC in 2020, David has worked extensively in SARS-CoV-2 classification, epidemiology, and genomics evaluation, including enhanced and uniform variant reporting. He has contributed more broadly to genomics reporting and analytical standardization and he has helped develop the podcast Behind the Biology, which he now hosts.
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