scientist, research platform lead @ArcadiaScience musician (nalle mishima/ryan york) record label (https://nitter.cf/t.co/3WBSAPL9pR)
San Francisco, CA
Joined May 2008
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Biology's first era of big data is coming to an end. Here's why that's actually a good thing — and what should come next. 🧵
thestacks.org/publications/i… [1/10]
Ryan York retweeted
Glass Box UMAP computes exact feature contributions for nonlinear dimensionality reduction, and we created a Python package to make it easy to use.
By @evankiefl @ryanayork @ArcadiaScience
[1/n]
Ryan York retweeted
Some thoughts @ArcadiaScience on a more Bayesian approach to bio data. Everyone seems to be running towards scale/speed, but I really think we're about to hit a hard wall of diminishing returns unless we reimagine our approaches and technologies for the next era.
"...the future of biological discovery won't belong to those who merely accumulate the largest haystacks or automate its brute force collection, but to those who develop the sharpest magnets for finding needles"
thestacks.org/publications/i…
Ryan York retweeted
Big day! We just dropped our 100th🎉 publication @ArcadiaScience!
Check out our latest👇
Our first coherent Raman spectroscopy dataset in live fission yeast at subcellular resolution
thestacks.org/publications/d…
An evolution-informed bioprospecting framework to facilitate mining the tree of life for bio-utility
thestacks.org/publications/p…
A Bayesian strategy for collecting biological data to maximize information gain
thestacks.org/publications/i…
Ryan York retweeted
Read the full pub from @ArcadiaScience for the framework, code, and data: thestacks.org/publications/i… [10/10]
Ryan York retweeted
You've heard that we're data-limited as machine learning models max out. But all data isn't of equal value. The structure and redundancy of that data matter for how well we can generalize.
Anyone who thinks about what data we need (and how much it costs) is going to want a strategy to do so. Here we walk you through an approach that takes into account how much new observations update our priors
Biology's first era of big data is coming to an end. Here's why that's actually a good thing — and what should come next. 🧵
thestacks.org/publications/i… [1/10]
The future of biological discovery won't belong to those who accumulate the largest haystacks, but to those who develop the sharpest magnets for finding needles. There's no excuse to gather data blindly anymore. [9/10]
Read the full pub from @ArcadiaScience for the framework, code, and data: thestacks.org/publications/i… [10/10]
🧵Really excited to share a set of our recent pubs @ArcadiaScience where we make black box BioML models transparent. [1/7]
research.arcadiascience.com/…