Arcadia Science
@ArcadiaScience · Berkeley, CA · joined 04 Jul 2021
Research and development company leveraging the biology of diverse organisms. Read about our science: https://t.co/IawT38WjQT
11 301Followers
45Following
901Posts total
216.9KViews on collected posts
Son gönderiler
Yeni gönderiler aranıyor…
Come help scale this and other raman tools!
Product Lead role now open: https://t.co/oJRvvT4LwH
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AI agent loop controlling our automated Raman microscope - from acquisition to stage movement to online analysis. It does a quick scan, then re-acquires spots with the best signal, and finally finds the most distinct spot and does an in-depth acquisition
@ArcadiaScience https://
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0:36
We also released a free organism illustration library sharing high quality CC0 illustrations of 70+ organisms & viruses (including chlamy and sea squirts): https://t.co/c9CHpJydem
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This spotlight is the second short video in our series highlighting organismal models. The first was on sea squirts:
https://t.co/2a8Q3t7dht
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Read more about our work with chlamy: https://t.co/tqSBmGurjC
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’Tis the season to be green 🌲 Our latest organism spotlight is Chlamydomonas reinhardtii — a tiny algae with a long history of punching above its weight in scientific discovery. Happy holidays!
https://t.co/t35Z9cCbOa
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Most importantly, first in our new series of organismal spotlight shorts (open source illustrations coming soon!). Sea squirts! https://t.co/ozfwFeb05f
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New website who dis https://t.co/HWbtJRCfr2
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One of our scientists whipped up a lit review terminal program where AI agents with different expertise collaboratively discuss @biorxivpreprint and @arxiv preprints 🤖🥼📚
https://t.co/xR0mHt00CO
Anyone here using an agent-based research tool you recommend?
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#ProteinCartography is an easy-to-use pipeline that identifies proteins related to a query protein using sequence- and structure-based searches, compares all protein structures, and creates an interactive map you can use to generate hypotheses. https://t.co/BQb9knflf9
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Is it possible to rapidly detect potential HGT events? Yes! #PreHGT is a pipeline that uses public, annotated, genomes from RefSeq and GenBank to build a pseudo-pangenome, detect outliers, annotate candidate genes, and report preliminary HGT candidates. https://t.co/7jB1pwagmc
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ICYMI, #NovelTree is a Nextflow pipeline for phylogenomic inference that outputs gene families, species trees, and more. Curious if a gene family is associated with a certain trait or have an idea of how to better infer gene families? Comment on the pub! https://t.co/vZBdF8oVsG
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Whether you’re performing phylogenomic inferences, identifying structural differences and similarities between proteins, or doing high-throughput time-lapse imaging, we have some free, easily accessible tools and resources that may be helpful for you. 🧵
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The phenotype-o-mat is a DIY, $400 plate imager that can do incident illumination and trans-illumination, and can hold optical filters for fluorescence assays. Its flexibility lets you gather growth, movement, fluorescence, and reflectance data. https://t.co/1yxmmFpbrn
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Interested in imaging the motility of organisms over time? Check out our agar microchambers:
- Only needs cheap (~$300), reusable PDMS stamps
- Different stamps let you image organisms of different sizes
- Made with agar and the media of your choice https://t.co/snb1wLMGgE
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You may have seen @ArcadiaScience’s protocol for the phenotype-o-mat, a $400 DIY plate imager, but I’m excited to share some details about how we designed and used this tool to gather growth, movement, fluorescence, and reflectance data. 🧵1/9
https://t.co/l1Bjf02Qb3 https://t.co/
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GIF
🚨 Introducing NovelTree: A Nextflow workflow for highly parallelized phylogenomic inference! 🚨
Pub:
https://t.co/MpSXsznkpv
GitHub (software):
https://t.co/vhbIDiRamj
GitHub (analysis code & walkthrough):
https://t.co/oDkv0NV3jC
@ArcadiaScience
A 🧵, 1/8 https://t.co/DwTsPEHxtz
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Ever wondered which organisms encode your favorite protein? 🤔 Do you like maps? 🗺️ At @ArcadiaScience, we’re developing “ProteinCartography,” a tool that makes interactive maps of protein space. We'd love your feedback on this early version! 🧵 1/9
https://t.co/DzxrPF2kjP
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We're on a never-ending quest to improve our experimental design, biological imaging, and image analysis! 🧪📸 Read more about how we confine swimming organisms within the field of view for better imaging [https://t.co/uXmYxTk81O]🐠🔍 [3/5]
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Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
70830 Apr
25K
1.3K
1.4K
576
3.4K21 Apr
4.9K1 Aug
9.5K5 Aug
8K25 Dec
135
981
870
3.5K20 Apr
1.4K29 Apr
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.56%30 Apr
0.16%
0.07%
0.14%
1.04%
0.67%21 Apr
0.79%1 Aug
0.87%5 Aug
0.21%25 Dec
2.22%
0.20%
0.80%
0.98%20 Apr
0.35%29 Apr
Reactions — likes, reposts, replies and quotes — divided by views.
What the audience does
Likes71.7%738 in total
Reposts20.9%215 in total
Replies2.1%22 in total
Bookmarks5.3%55 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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