iiinova — where your digital self keeps evolving

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Joey Bose @joeybose.bsky.social · 11/09/2025

📢 Interested in doing a PhD in generative models 🤖, AI4Science 🧬, Sampling 🧑‍🔬, and beyond? I am hiring PhD students at Imperial College London for the next application cycle. 🔗See the call below: joeybose.github.io/phd-positions/ ✨ And a light expression of interest: forms.gle/FpgTiuatz9ft...

joeybose.github.io

Joey Bose

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Vikram Agarwal @vagar.bsky.social · 25/07/2025

Very excited that our most significant work, a collaboration w/ Dr. Can Cenik at UT Austin on translational gene regulation, was finally published in Nature Biotechnology in a dual set of studies: Paper 1 -- an AI model trained to predict translation rates from mRNA sequences: rdcu.be/exN1l

url.de.m.mimecastprotect.com

Predicting the translation efficiency of messenger RNA in mammalian cells

Nature Biotechnology - A deep convolutional neural network model predicts the influence of the full-length mRNA sequence on translation efficiency.

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Ian Shi @heyitsmeianshi.bsky.social · 15/07/2025

We're excited to release 𝐦𝐑𝐍𝐀𝐁𝐞𝐧𝐜𝐡, a new benchmark suite for mRNA biology containing 10 diverse datasets with 59 prediction tasks, evaluating 18 foundation model families. Paper: biorxiv.org/content/10.1... GitHub: github.com/morrislab/mR... Blog: blank.bio/post/mrnabench

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taykhoomdalal.bsky.social @taykhoomdalal.bsky.social · 15/07/2025

We are excited to introduce mRNABench, a comprehensive benchmarking suite that we used to evaluate the representational capabilities of 18 families of nucleotide foundation models on mature mRNA specific tasks. Paper: doi.org/10.1101/2025... Code: github.com/morrislab/mR... A 🧵

doi.org

mRNABench: A curated benchmark for mature mRNA property and function prediction

Messenger RNA (mRNA) is central in gene expression, and its half-life, localization, and translation efficiency drive phenotypic diversity in eukaryotic cells. While supervised learning has widely bee...

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David A Knowles @davidaknowles.bsky.social · 03/07/2025

New work from the lab trying to wrap our heads around the massive complexity of the human transcriptome revealed by long-read RNA-seq! Fun collab with Gloria Sheynkman. www.biorxiv.org/content/10.1...

biorxiv.org

Perplexity as a Metric for Isoform Diversity in the Human Transcriptome

Long-read sequencing (LRS) has revealed a far greater diversity of RNA isoforms than earlier technologies, increasing the critical need to determine which, and how many, isoforms per gene are biologic...

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Quaid Morris @quaidmorris.bsky.social · 03/06/2025

Please check out our new approach to modeling somatic mutation signatures. DAMUTA has independent Damage and Misrepair signatures whose activities are more interpretable and more predictive of DNA repair defects, than COSMIC SBS signatures 🧬🖥️🧪 www.biorxiv.org/content/10.1...

biorxiv.org

Damage and Misrepair Signatures: Compact Representations of Pan-cancer Mutational Processes

Mutational signatures of single-base substitutions (SBSs) characterize somatic mutation processes which contribute to cancer development and progression. However, current mutational signatures do not ...

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David A Knowles @davidaknowles.bsky.social · 27/01/2025

#MLCB2025 will be Sept 10-11 at @nygenome.org in NYC! Paper deadline June 1st & in-person registration will open in May. Please sign up for our mailing list groups.google.com/g/mlcb/ for future announcements. More details at mlcb.github.io. Please RP!

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Jay Alammar @jayalammar.bsky.social · 27/01/2025

The Illustrated DeepSeek-R1 Spent the weekend reading the paper and sorting through the intuitions. Here's a visual guide and the main intuitions to understand the model and the process that created it. newsletter.languagemodels.co/p/the-illust...

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Gunnar Rätsch @gxxxr.bsky.social · 18/12/2024

Where RNA Science Meets AI, May 4–8, 2025, Ascona. Invited speakers: @evamarianovoa.bsky.social @fabiantheis.bsky.social @rivaselenarivas.bsky.social, Sterling Churchman, Barbara Treutlein, Rahul Satijia, Registration open www.rna-ai.org @hagentilgner.bsky.social @quaidmorris.bsky.social

rna-ai.org

RNA-AI 2025

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phil-fradkin.bsky.social @phil-fradkin.bsky.social · 17/12/2024

Thanks to the FM4Science workshop at #Neurips for recognizing MolPhenix as best paper! We had so much fun working on this with Puria (co-first author), @karush17.bsky.social, Frederik and co-supervised by Maciej and @dom-beaini.bsky.social arxiv.org/abs/2409.08302 @valenceai.bsky.social

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phil-fradkin.bsky.social @phil-fradkin.bsky.social · 15/12/2024

Excited to be presenting Orthrus with Ruain Shi and Keren Isaev @karini925.bsky.social today! We will be presenting our spotlight at the workshop on AI for new drug modalities #NeurIPS2024 Come chat about a new approach to mRNA representation learning!

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phil-fradkin.bsky.social @phil-fradkin.bsky.social · 09/12/2024

I’ll be at #NeurIPS presenting two new papers on self-supervised approaches for cellular representation learning! 1. MolPhenix (main track): Multi-modal learning learning joint representations between molecular structures & phenomic data

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Anshul Kundaje @anshulkundaje.bsky.social · 09/12/2024

My conclusion: We should pay attention to train/test splits, not blindly follow standard benchmarks which are often very flawed in many applied ML areas, not hype up early results. We should be more collaborative, be generous with credit, give benefit of the doubt & be less adversarial

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