The MicroBinfie podcast discusses the top programming languages for bioinformatics. Andrew, Lee, and Nabil agree that Python is a great starting point for its consistency and rigor. Its strict syntax is ideal for teaching programming fundamentals that are essential in any language. In contrast, Perl encourages multiple ways of doing the same thing, creating confusion and difficulties in keeping track of things.

The hosts caution against starting with trendy languages that are constantly changing. Instead, stick with more established languages like Python, which have established libraries and concepts that will help you advance more easily. Trendy languages come and go like changing tides, making them riskier choices. Additionally, they highlight the importance of understanding databases and their primary keys and unique fields. SQL is useful, particularly in dealing with large datasets. It is consistent across flavors and unlikely to go away soon. It takes a lot of skill to optimize queries to work in milliseconds.

The hosts emphasize that the language you choose to learn depends on your individual goals and environment. For instance, Lee suggests that you should look to who is in your space and what they are using and who is willing to help you. Once you understand the programming concepts, it is easier to transfer them to other languages, and it is just a question of understanding the syntax.

Andrew, Lee, and Nabil also discuss their own trajectories of learning programming languages, revealing that it takes a long time to become an expert in a language, and it is something that needs to be appreciated. They highlight the difference between just learning the basics of a language and really getting into the depths of it and the frameworks and libraries.

The hosts also mention languages that are important to pick up, like SQL and bash scripting, and languages that are popular for web development, like JavaScript. However, they caution that JavaScript and Java are not the same thing and that JavaScript has a reputation for being a weird language.

When asked what language they would choose for a task, Nabil says he would use Perl, Lee mentions R for stats, while Andrew admits that he has to relearn R every time he comes back to it and therefore prefers Perl for quick scripts. They also discuss their love-hate relationship with R, mentioning that while it has useful libraries like GGplot and GGtree, its syntax is difficult to work with and has separate paradigms of approaching the same problem.

The hosts conclude by acknowledging that there is no one-size-fits-all approach to learning programming languages. One should choose based on their goals, environment, and personal preferences. Python is a useful language to learn, even if one is not interested in bioinformatics. Additionally, they note that the fundamentals of databases and how they work are crucial to understand and utilized across fields.

Encore: What language should I learn?

Kevin Libuit began his career in public health bioinformatics in Virginia, USA, while Andrew Page's experience mainly leans towards the academic side.
   
Differences between Academia and Public Health:
   - Academia is flexible, allows for experimentation, and tends to focus on niche, blue-sky research.
   - Public health emphasizes quality, validation, reproducibility, and the impact on real-world actions, such as informing government responses or legal actions related to health concerns.

Tool Development and Use:
   - Academia often reinvents tools, leading to many solutions for the same problem.
   - Public health focuses on the implementation and consistent use of tools for actionable insights.
   - Challenges arise when academic tools are left unsupported after their initial development, whereas public health relies on long-term tool support.
   - Containerization, like Docker, helps maintain a consistent and reproducible tool environment.
   
Training and Workforce:
   - Academia tends to be cutting-edge, while public health focuses on stability and intent.
   - Upskilling public health scientists to use bioinformatics tools is crucial, often emphasizing tool usage rather than deep technical understanding.
   
Collaboration:
   - Close collaboration between academia and public health yields the best outcomes.
   - Such collaborations help in aligning the innovation from the academic world with the real-world applications in public health.
   
Publication:
   - Manuscripts pull together all elements of a study, ensuring clarity, validity, and ease of implementation across different labs. They help translate work from one public health lab to another.

Conclusion: The episode delved into the distinctions and overlaps between academic and public health bioinformatics, highlighting the importance of collaboration and communication between the two realms.

Ep5 Public Health Perspective

Hosts Kevin Libuit and Andrew Page discuss public health bioinformatics.
- They delve into the regional differences in the implementation of bioinformatics in public health, comparing the U.S. and the U.K.
- Kevin shares his experience from the Virginia State Public Health Sciences. In 2016, public health labs in the U.S. began transitioning from traditional techniques to whole genome sequencing.
- Kevin was one of the first bioinformatics scientists in Virginia and was part of a small group of state-level bioinformatics scientists. 
- Challenges faced by states in bioinformatics implementation weren't always easily addressed by federal bodies like the CDC due to state-specific issues.
- The group of state-level bioinformatics scientists, including Kevin, formed a consortium named StaPH-B to share their experiences and challenges.
- The podcast touches on the roles of federal bodies like the FDA and CDC and the complexities they bring.
- Andrew then provides insights into the U.K.'s public health structure, noting the differences between nations like Scotland, England, Wales, and Northern Ireland.
- The discussion pivots to the importance and challenges of data sharing, both in the U.S. and Europe.
- The hosts also touch on the importance of bioinformatics in solving outbreaks, with a mention of the Artic network which provides expertise during health crises.
- The episode concludes with Kevin mentioning projects like the StaPH-B Docker builds and the potential for more collaborations in the future.

Ep 6 Regional Differences in  Public Health

Hosted by Kevin Libuit and Andrew Page, the podcast focuses on the evolution of tech adoption in pathogen genomics. The narrative begins with the shift from traditional software packages to modern cloud-based GUIs. Early software installations were cumbersome, often taking weeks and requiring an in-depth understanding of dependencies and compilers. There was also a notable shift in programming languages from Ruby and Perl to Python. Package managers evolved from systems like Debian and Homebrew to Conda and BioConda, with Mamba offering further installation improvements. The podcast touched on the use of Make as an early workflow manager and its evolution to tools like snake make, next flow, and Galaxy. The role of GUIs in democratizing access to bioinformatics tools and the transition from on-prem servers to cloud computing was also discussed. However, there were concerns about the security implications of cloud computing in certain countries. The episode also delved into the challenges of closed-source tools and emphasized the benefits of open-source alternatives, especially those funded by public money. Finally, the potential influence of AI and machine learning on genomics was explored, acknowledging initial resistance but recognizing the inevitable integration of these technologies in the future. The podcast highlighted the tech journey in pathogen genomics, the significance of open-source tools, and the exciting prospects brought about by AI and machine learning.

Ep 7 Technological Advancements in public health bioinformatics

A quick update from Andrew from the Global Microbial Identifier conference in Vancouver, Canada.

Ep8 Global Microbial Identifier in a nutshell

The podcast, set against the picturesque backdrop of Vancouver, delves into the intricate world of bioinformatics, emphasizing the pivotal role of the Global Microbial Identifier (GMI) in facilitating discussions on data sharing, public health, and international collaborations. Organizers Emma and Will, along with other professionals underscore the challenges in data sharing due to varied international laws, privacy concerns, and technical roadblocks. A significant highlight was the discourse on the importance of respecting the data rights of indigenous and marginalized communities, particularly the First Nations, and the ethical considerations surrounding it. Moreover, the collaboration with Lebanon on SARS-CoV-2 research exemplified the global cooperative spirit. While technical advancements were celebrated, the podcast accentuated the persistent policy challenges and the quintessential value of face-to-face interactions in conferences to foster personal and professional relationships in the realm of bioinformatics.

Sorry about the audio quality, we were outdoors and our microphones weren't working as intended.

Ep 9 Update from Global Microbial Identifier

In this episode of the Bioinformatics Lab podcast, hosted by Kevin Libuit and Andrew Page from Theiagen, the primary focus is on COG-UK. COG-UK stands out as a premier consortium for SARS-CoV-2 sequencing and set the benchmark for many international groups during the COVID-19 pandemic, especially in the realms of sequencing, analysis, and reporting.

Andrew Page, having played a pivotal role in COG-UK, sheds light on its inception, objectives, and background. Contrary to its grand impression, COG-UK was majorly formed by professionals already acquainted with each other from the UK genomics arena. By March 2020, there was a pressing demand to initiate sequencing. Andrew recalls being at the Quadram Institute, strategizing on primers for SARS-CoV-2 based on the set released by Artic. Preliminary plans were sketched out for testing and sequencing, even as they awaited test samples.

Ep 10 COG-UK: Pioneering SARS-CoV-2 Sequencing during the Pandemic

In this episode of the Bioinformatics Lab podcast, Kevin Libuit and Andrew Page delve deep into the significant impacts of COG-UK during the COVID-19 pandemic. Highlighting a groundbreaking paper by Dr Dinesh Aggarwal from the University of Cambridge, they discuss the role of genomic data in assessing quarantine measures to prevent the importation and spread of SARS-CoV-2. Discover how genomics painted a clearer picture of new virus lineages entering the UK and how these insights influenced government policies. Dr Aggarwal won the Royal College of Pathologists (RCPath) Silver Research Medal for this work. Join us as we explore the fusion of science and policy, demonstrating the unprecedented power of genomics in real-world applications. 

Award: https://www.med.cam.ac.uk/peacock/rcpath-research-medal-winners-2022-dinesh-aggarwal/
Paper: https://www.nature.com/articles/s41467-022-28371-z

Ep 11 Genomics informed pandemic policy

Genotyping is at the foundation of modern microbiology. We discuss all of the techniques used in the preNGS era.

04 History of Genotyping - The early years

Modern genotyping is discussed in this second part.

05 History of Genotyping - Decentralised Future

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00 Trailer

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 Katz from the Centres for Disease Control and Prevention (US), Dr. Nabil-Fareed Alikhan from the University of Oxford (UK), and Prof. Andrew Page from Theiagen Genomics (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 Centres for Disease Control and Prevention, University of Oxford or Theiagen Genomics.

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.com

Encore: What language should I learn?

Micro Binfie Podcast

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