Biodatascience101

Fundamental biological data-science made easy.
A teaching initiative by #SinoDanishCenter and @DTU_HealthTech
#biodatascience101

[Biodatascience101 @Biodatascience1]

Sign-up is closing soon (16th November)! Join us to learn state-of-the-art clustering and visualization techniques on SARS-CoV2 antibodies using Python and JupyterLab!

Join our online workshop on 25th November 9:00-15:40 CET. Sign-up here: https://t.co/r3mxlQbVqI

[Biodatascience101 @Biodatascience1]

We are back with our third online workshop, focusing on using state-of-the-art clustering and visualization techniques, to see what anti-SARS-CoV2 antibodies look like!
Join our online workshop on 25th November 9:00-15:40 CET. Sign-up here: https://t.co/r3mxlQbVqI

[Michael Hoffman @michaelhoffman.bsky.social @michaelhoffman]

I've tried this "artificial intelligence" plant identification app multiple times on the same tree and get a different answer each time. They must be using random forest

[Abhinav Mishra @shadytoyou]

Just attended @Biodatascience1’s #Workshop on “#MachineLearning Classification of Benign and Malignant #Tumour”. Some highlighted remarks by @ai_mlab, @vanessa_jurtz, and Rudi Agius:

[Biodatascience101 @Biodatascience1]

Just 5 more days to register for our second #Biodatascience101 workshop, introduction to #MachineLearning with an expert panel discussion from @novonordisk and @Rigshospitalet. 30th June 0900-1230 CET, with fundamental methods generalizing to all datasets.
https://t.co/Ovh7aNo8xv

[Biodatascience101 @Biodatascience1]

What is your bioinformatics stack?

[Biodatascience101 @Biodatascience1]

I have no choice but to use my secret weapon!
....
"how to count fasta sequences site:https://t.co/21qO8fIwHi"

https://t.co/pv04lB9bE2

[Biodatascience101 @Biodatascience1]

Vacation period is coming!

[Biodatascience101 @Biodatascience1]

Biodatascience101: A surprisingly accurate definition for an entirely AI generated word!

https://t.co/Hfnn6gYxm6

[Biodatascience101 @Biodatascience1]

Yes, you!

[Biodatascience101 @Biodatascience1]

Registrations are open for our live introduction to #MachineLearning on tumor imaging features in #Jupyter notebooks, with model analysis in @scikit_learn !! Teaching directly in your browser. Join our online workshop on 30th June 0900-1230 CET. Sign-up: https://t.co/Jai8TPW6pe

[Biodatascience101 @Biodatascience1]

This team almost won a 25 000 USD kaggle competition. They shared an excellent write-up and Jupyter notebooks with code on how they predicted open ion channels from electrical signals using hidden markov models. @Gillesvdwiele

https://t.co/nkh9ktAW0Q

[Biodatascience101 @Biodatascience1]

Murphy´s law: Whatever can go wrong will go wrong. Unless you expect it to go wrong...

[Biodatascience101 @Biodatascience1]

Remember: if your model is bad enough, the confidence intervals can fall outside the printable area!

https://t.co/uyngZAXMLj

[Biodatascience101 @Biodatascience1]

To all #structuralbiology fans: How to use Chimera @UCSFChimeraX for protein structural analysis. @rcsbPDB

https://t.co/YsBrcPffy8

[Daphne Truan @DaphneTruan]

We are hiring!

Data Scientist - Structural Bioinformatics - Cambridge UK
https://t.co/yjVpa642ky

#Jobs #Bioinformatics #DataScience #MachineLearning #Biostatistics #SoftwareEngineering #structuralbiology @LonzaGroup

[Biodatascience101 @Biodatascience1]

Incredible #CryoEM capturing of a protein directly inside the cell!

[Biodatascience101 @Biodatascience1]

.@xkcdComic "This document was probably prepared by a professional, because no normal human trying to communicate in 2020 would choose this
ridiculous format"

https://t.co/Nx6aFT5TRf

[Biodatascience101 @Biodatascience1]

Type III error: Undefined - but could be a result of mistaking tally marks for Roman numerals.

[Biodatascience101 @Biodatascience1]

2010 and 2020 by #XKCD

https://t.co/Zv4cx98O10