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Please join us for our next RNA CASP SIG with Shujun He:

„Ribonanza: deep learning of RNA structure through dual crowdsourcing”

This is follow-up to our previous talk of Rhiju Das (https://www.youtube.com/watch?v=R6-MwrGkj7M&)

[Zoom](https://urldefense.proofpoint.com/v2/url?u=https-3A__stanford.zoom.us_j_93445935624-3Fpwd-3DK0VUWk0zaVNMZlU1U0xUMS8vSWUwZz09&d=DwMFaQ&c=WO-RGvefibhHBZq3fL85hQ&r=0lUjW57N1liiDVO5wzD9g5qjic3xcIQ5O7wLU7r81hA&m=arbubYGVlHU7r5U62CgEmarGmxHnOtTysQwN9aCJsuHl9sQym0QFMDa2Gn41dEdZ&s=3rWBZ-vu-LrB-wgVAUts27AvWDWJFR6IEQNM23lG4eM&e=) link Tuesday Feb 13th Pacific Time 8 am / Eastern Time 11 am / Central European Time: 5 pm / China Standard Time: 11 pm

If you have recommendations on topics of discussion or speakers, please feel free to email us as well.

We have also recently implemented a [schedule](https://urldefense.proofpoint.com/v2/url?u=https-3A__tinyurl.com_rna-2Dsig-2Dschedule&d=DwMFaQ&c=WO-RGvefibhHBZq3fL85hQ&r=0lUjW57N1liiDVO5wzD9g5qjic3xcIQ5O7wLU7r81hA&m=arbubYGVlHU7r5U62CgEmarGmxHnOtTysQwN9aCJsuHl9sQym0QFMDa2Gn41dEdZ&s=xrR8IIYhN9IQ0VlVjc_-o3oEldm_GbVPpvHEIGeihHw&e=) to view past and upcoming seminars, as well as a calendar [(google](https://urldefense.proofpoint.com/v2/url?u=https-3A__tinyurl.com_rna-2Dsig-2Dcalendar&d=DwMFaQ&c=WO-RGvefibhHBZq3fL85hQ&r=0lUjW57N1liiDVO5wzD9g5qjic3xcIQ5O7wLU7r81hA&m=arbubYGVlHU7r5U62CgEmarGmxHnOtTysQwN9aCJsuHl9sQym0QFMDa2Gn41dEdZ&s=lkoboo6d_x60maIZC4BobSkhETuYI2_H2Yk2Q3ZJDSI&e=) [outlook)](https://urldefense.proofpoint.com/v2/url?u=https-3A__tinyurl.com_rna-2Dsig-2Dcal-2Dics&d=DwMFaQ&c=WO-RGvefibhHBZq3fL85hQ&r=0lUjW57N1liiDVO5wzD9g5qjic3xcIQ5O7wLU7r81hA&m=arbubYGVlHU7r5U62CgEmarGmxHnOtTysQwN9aCJsuHl9sQym0QFMDa2Gn41dEdZ&s=RF0zJUjFA35qyo92Uq6Yt-fty5C1Nm2J5WJJDb5uJwA&e=) which can be added to automatically have events added to your calendar. Hopefully these will help everyone keep up to date.

See you soon,

Rachael Kretsch (Rhiju Das and Wah Chiu labs @Stanford)
Marcin Magnus (Elena Rivas lab @Harvard)

For recording see playlist on [YouTube @CASPRNASIG](https://www.youtube.com/@CASPRNASIG).

Zoom link: https://stanford.zoom.us/j/93445935624?pwd=K0VUWk0zaVNMZlU1U0xUMS8vSWUwZz09

# Abstract

Prediction of RNA structure from sequence remains an unsolved problem, and progress has been slowed by a paucity of experimental data. Here, we present Ribonanza, a dataset of chemical mapping measurements on two million diverse RNA sequences collected through Eterna and other crowdsourced initiatives. The Ribonanza measurements enabled solicitation, training, and prospective evaluation of diverse deep neural networks through a Kaggle challenge, followed by distillation into a single, self-contained model called RibonanzaNet. When fine tuned on previous datasets, RibonanzaNet achieves state-of-the-art performance in modeling RNA chemical stability and RNA secondary structure. The latter enables three-dimensional structure modeling of RNA-only targets from the recent CASP trials with accuracy approaching human expert groups.

# Bio

Shujun He is a PhD student in chemical engineering at Texas A&M University. Interested in applying deep learning to scientific problems. Ranked 17/194,534 (top 0.008%) globally on Kaggle (https://www.kaggle.com/shujun717), the biggest machine learning competition platform
