Formalizing our commitment to code sharing In support of open science, PLOS Biology routinely asks authors to openly share their research code before publication. We are now formalizing this practice with a mandatory code sharing policy and…

In support of #OpenScience, we routinely ask authors to openly share their #research #code before publication.

We are now formalizing this practice with a mandatory #CodeSharing policy and clarifying what we mean by code sharing.

#quarto template for bioRxiv preprints, inspired by @henriqueslab.bsky.social

github.com/chi-raag/bio...

New blog post inspired by work from @konczerj.bsky.social
chiraaggohel.com/posts/llms-s...

"Your AI can’t see gorillas!"
A few years ago we found that students are more likely to see the gorilla in their data if they are not also asked to test a specific hypothesis. In his blog Chiraag Gohel now shows that Chat-GPT can’t help you to find it either.
chiraaggohel.com/posts/llms-e...

Univariate-Guided Sparse Regression In this paper, we introduce ``UniLasso'' -- a novel statistical method for sparse regression. This two-stage approach preserves the signs of the univariate coefficients and leverages their magnitude. ...

I am happy to announce our new paper "Univariate-guided sparse regression". It's a new lasso that leverages the signs and magnitude of univariate coefficients .
Sparser and more interpretable than the lasso. We're excited! arxiv.org/abs/2501.18360
R: github.com/trevorhastie...

Your AI Can't See Gorillas Discussion

I guess the title of Chiraag's report gives away the result! But it's a good read anyhow: chiraaggohel.com/posts/llms-e...
Original Yanai & Lercher 2020 paper: genomebiology.biomedcentral.com/articles/10....

Now that LLM-based AI tools can analyze data on their own, @chiraag.bsky.social decided to test whether they notice the gorilla, or whether they also seem to experience inattentional blindness—like humans who fail to notice the "invisible gorilla" that @profsimons.bsky.social and I wrote about ...

Generalized linear neural network models
statmodeling.stat.columbia.edu/2025/02/04/g...

Had such an enriching time at #cshldata24! I hope I convinced some of the bright minds there to think about applying their work and skills towards making sense of metabolomics data 🧪🤓

~~ new blog post ~~

i wrote about the meme that academic code is bad, what i think is achievable, and why i don't think we should be trying to get academics to write software for production

would love to hear what folks think!

#rstats #pydata

www.alexpghayes.com/post/what-i-...