Micro binfie podcast Podcast Por Microbial Bioinformatics arte de portada

Micro binfie podcast

Micro binfie podcast

De: Microbial Bioinformatics
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Microbial Bioinformatics is a rapidly changing field marrying computer science and microbiology. Join us as we share some tips and tricks we’ve learnt over the years. If you’re student just getting to grips to the field, or someone who just wants to keep tabs on the latest and greatest - this podcast is for you. The hosts are Dr. Lee - a bioinformatician in the United States, Dr. Nabil-Fareed Alikhan from the University of Oxford (UK), and Prof. Andrew Page from Origin Sciences (UK) and bring together years of experience in microbial bioinformatics. The opinions expressed here are our own and do not necessarily reflect the views of University of Oxford or Origin Sciences. Intro music : Werq - Kevin MacLeod (incompetech.com) Licensed under Creative Commons: By Attribution 3.0 License http://creativecommons.org/licenses/by/3.0/ Outro music : Scheming Weasel (faster version) - Kevin MacLeod (incompetech.com) Licensed under Creative Commons: By Attribution 3.0 License http://creativecommons.org/licenses/by/3.0/ Question and comments? microbinfie@gmail.comAll rights reserved Ciencia
Episodios
  • 152 - Deacon part 2

    152 - Deacon part 2
    Apr 9 2026
    In this follow-up Software Deep Dive episode, we continue our conversation with Dr. Bede Constantinides (University of Birmingham) about the design and implementation of Deacon, a fast host-read removal tool for metagenomics. Deacon uses minimizers and k-mer set membership queries instead of alignment, allowing it to filter reads extremely quickly while balancing sensitivity and specificity. The tool is written in Rust, producing a small, fast binary and enabling very high throughput. We also discuss benchmarking with diverse viral and bacterial datasets, why tools like Kraken2 are not always ideal for host depletion, and why host read removal remains an unsolved problem—especially when balancing privacy, computational cost, and preservation of microbial reads. Links Deacon https://github.com/bede/deacon Hostile https://github.com/bede/hostile/ Bede Constantinides http://bede.im/ Kraken2 https://ccb.jhu.edu/software/kraken2/
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    28 m
  • 151 - Deacon part 1

    151 - Deacon part 1
    Mar 26 2026
    In this Software Deep Dive episode, we talk with Dr. Bede Constantinides (University of Birmingham) about Deacon, a tool for removing host DNA reads from metagenomic datasets. We discuss why host read removal is a deceptively difficult problem, the limitations of alignment-based approaches, and how Deacon evolved from Bede's earlier tool Hostile. The conversation covers practical issues such as human contamination in metagenomes, balancing sensitivity vs specificity when filtering reads, and the computational challenges of working with large human reference datasets and pangenomes. This episode focuses on the background and motivation for Deacon. The next episode will dive deeper into how the method works. Links Deacon https://github.com/bede/deacon Hostile https://github.com/bede/hostile/ Bede Constantinides http://bede.im/ nf-core taxprofiler https://nf-co.re/taxprofiler Kraken2 https://ccb.jhu.edu/software/kraken2/
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    24 m
  • 150 - Genomicx

    150 - Genomicx
    Mar 12 2026
    In this episode, Lee, Nabil, and Andrew experiment with “vibe coding” bioinformatics tools using AI coding assistants. The goal: quickly build useful genomics utilities that run entirely in the browser via WebAssembly, without requiring command-line installs or servers. Nabil states: “Even if you don’t want to use this technology, you should pay attention - because everyone else will.” They discuss how existing bioinformatics programs can be compiled to WebAssembly and wrapped with simple browser interfaces so analyses run locally on a user’s machine. This keeps genomic data private while making tools easier to access. The prototype tools discussed in the episode are available here: https://genomicx.vercel.app/ These examples show how browser-based bioinformatics might work for lightweight tasks such as genome comparisons and basic sequence analysis. Topics Covered * Using AI tools to rapidly prototype bioinformatics software * Compiling genomics programs to WebAssembly * Running analyses locally in the browser * Privacy advantages of keeping genomic data on the user’s computer * Practical limits of browser-based computation Try the tools and let us know what you think using the hashtag #genomicx
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    43 m
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