What we're about

We meet to talk and do science at Boston's Open Science Laboratory - BosLab.

http://www.boslab.org

Located on 2400 Massachusetts Avenue in Cambridge, BosLab is your community DIYbio lab! We engineer yeast, sequence soil microbes, and generally host projects and events focused around synthetic, molecular, micro, and general biology. Come engineer living organisms with us!

Upcoming events (5)

Synthetic Biology Journal Club

Online event

Synthetic Biology Journal Club with interests ranging from biocomputation to terraforming. Passion for biology required.

More details:
Papers will be mostly recent publications in an effort to keep up with the field. Having read the material prior to the meetup is encouraged.

Schedule:
7:30pm – 9:00pm, every other week.

Useful apparatus:
A printed copy of the paper or a laptop (preferably both).

Important to know:
Papers will be disseminated through and journal club will be held in our Discord.

Discord: https://discord.gg/BRNguhy

R for Data Science (Part 3): From Data Import to Tidy and Relational Data

This learning circle co-organized with P2PU (https://www.p2pu.org/en/ ) will use the free "R for Data Science" book by Hadley Wickham and Garrett Grolemund (https://r4ds.had.co.nz/ ) and the community-contributed "R for Data Science Exercise Solutions" book by Jeffrey Arnold (https://jrnold.github.io/r4ds-exercise-solutions/index.html ). We will cover chapters 9-13 continuing from where we left off in the second "R for Data Science" learning circle. The meetings will consist of an interactive lecture with live coding and small-group exercise breaks.

Prerequisite:
To join this learning circle, you should have participated in the previous "R for Data Science" learning circle or be familiar with the material in chapters 1-8 of the "R for Data Science" book. If you need help learning or revising these chapters, please email me at sebastien. vigneau[AT]gmail.com.

Sign-up:
To join this learning circle, sign-up on the P2PU website is mandatory. The sign-up link is: https://learningcircles.p2pu.org/en/signup/online-1768/ . Each meeting will build on the previous ones, so participants are asked to attend every meeting or work on their own the sections they may miss.

When:
This learning circle meets every Wednesday from 7 pm to 9 pm EDT starting July 21st, 2021, for 6 weeks.

Where:
We will meet on Zoom. The link will be sent by email after you sign up on the P2PU website.

Course material we will use:
"R for Data Science" (https://r4ds.had.co.nz/ ) teaches how to do data science with R. Chapters cover how to import, tidy, transform, visualize, model, and communicate data. The general philosophy is to teach the most useful skills first, using an abundance of examples and exercises. Solutions to the exercises can be found in a community-contributed book by Jeffrey Arnold (https://jrnold.github.io/r4ds-exercise-solutions/ ).

Links:
Sign-up form on P2PU: https://learningcircles.p2pu.org/en/studygroup/1768/
P2PU website: https://www.p2pu.org/en/
"R for Data Science" by Hadley Wickham and Garrett Grolemund: https://r4ds.had.co.nz/
"R for Data Science Exercise Solutions" by Jeffrey Arnold and Contributors: https://jrnold.github.io/r4ds-exercise-solutions/index.html
"Install R and RStudio" by Data Carpentry: https://datacarpentry.org/R-ecology-lesson/#install-r-and-rstudio

R for Data Science (Part 3): From Data Import to Tidy and Relational Data

This learning circle co-organized with P2PU (https://www.p2pu.org/en/ ) will use the free "R for Data Science" book by Hadley Wickham and Garrett Grolemund (https://r4ds.had.co.nz/ ) and the community-contributed "R for Data Science Exercise Solutions" book by Jeffrey Arnold (https://jrnold.github.io/r4ds-exercise-solutions/index.html ). We will cover chapters 9-13 continuing from where we left off in the second "R for Data Science" learning circle. The meetings will consist of an interactive lecture with live coding and small-group exercise breaks.

Prerequisite:
To join this learning circle, you should have participated in the previous "R for Data Science" learning circle or be familiar with the material in chapters 1-8 of the "R for Data Science" book. If you need help learning or revising these chapters, please email me at sebastien. vigneau[AT]gmail.com.

Sign-up:
To join this learning circle, sign-up on the P2PU website is mandatory. The sign-up link is: https://learningcircles.p2pu.org/en/signup/online-1768/ . Each meeting will build on the previous ones, so participants are asked to attend every meeting or work on their own the sections they may miss.

When:
This learning circle meets every Wednesday from 7 pm to 9 pm EDT starting July 21st, 2021, for 6 weeks.

Where:
We will meet on Zoom. The link will be sent by email after you sign up on the P2PU website.

Course material we will use:
"R for Data Science" (https://r4ds.had.co.nz/ ) teaches how to do data science with R. Chapters cover how to import, tidy, transform, visualize, model, and communicate data. The general philosophy is to teach the most useful skills first, using an abundance of examples and exercises. Solutions to the exercises can be found in a community-contributed book by Jeffrey Arnold (https://jrnold.github.io/r4ds-exercise-solutions/ ).

Links:
Sign-up form on P2PU: https://learningcircles.p2pu.org/en/studygroup/1768/
P2PU website: https://www.p2pu.org/en/
"R for Data Science" by Hadley Wickham and Garrett Grolemund: https://r4ds.had.co.nz/
"R for Data Science Exercise Solutions" by Jeffrey Arnold and Contributors: https://jrnold.github.io/r4ds-exercise-solutions/index.html
"Install R and RStudio" by Data Carpentry: https://datacarpentry.org/R-ecology-lesson/#install-r-and-rstudio

Virtual Open House

Online event

Join us for a virtual open house!

Due to COVID-19, our monthly open houses are now held online.
Meet with Boslab members to learn more about the DIY biology movement and our community lab. Our mission is to make science accessible to everyone! If you want to tour the lab “in person” please message us on Meetup or email [masked] to schedule a visit.

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