R, Data Science, & Computational Biology

We’re partnering with the upcoming R Conference, because the R Conference is well… amazing! Tons of great AI content, and they were nice enough to connect us to Daniel Chen for this episode. He discusses data science in Computational Biology and his perspective on data science project organization.

Sponsors:

• DigitalOcean – DigitalOcean’s developer cloud makes it simple to launch in the cloud and scale up as you grow. They have an intuitive control panel, predictable pricing, team accounts, worldwide availability with a 99.99% uptime SLA, and 24/7/365 world-class support to back that up. Get your $100 credit at do.co/changelog. 
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Featuring:

• Daniel Chen – Website, GitHub, X
• Chris Benson – Website, GitHub, LinkedIn, X
• Daniel Whitenack – Website, GitHub, X

Show Notes:

R Conference:

• Website
• Twitter: @rstatsdc
• Tickets
• Discount code PRACTICALAI20 is good for 20% off every ticket type, including the conference & all workshops

Links relevant to the show:

• William Stafford Noble 2009 - A Quick Guide to Organizing Computational Biology Projects
• Greg Wilson, et al. 2014: “Best Practices for Scientific Computing”
• Greg Wilson, et al. 2017: “Good enough practices in scientific computing”
• Jenny Bryan’s code smells: link 1 and link2
• Jenny Bryan on naming things
• JD Long’s talk at rstudio::conf this year about being empathetic
• python’s version of pyprojroot
• “Be kind: all else is details”. – Greg Wilson, Teaching Teach Together – The Rules

Books

• “Pandas for Everyone” by Daniel Chen
• “Advanced R” by Hadley Wickham

Upcoming Events: 

• Register for upcoming webinars here!