gRNAde: Geometric Deep Learning for 3D RNA inverse design

1 code implementation • 24 May 2023 • Chaitanya K. Joshi, Arian R. Jamasb, Ramon Viñas, Charles Harris, Simon V. Mathis, Alex Morehead, Rishabh Anand, Pietro Liò

Computational RNA design tasks are often posed as inverse problems, where sequences are designed based on adopting a single desired secondary structure without considering 3D geometry and conformational diversity.

Pretrained Encoders are All You Need

1 code implementation • ICML Workshop URL 2021 • Mina Khan, P Srivatsa, Advait Rane, Shriram Chenniappa, Rishabh Anand, Sherjil Ozair, Pattie Maes

Data-efficiency and generalization are key challenges in deep learning and deep reinforcement learning as many models are trained on large-scale, domain-specific, and expensive-to-label datasets.

Contrastive Learning reinforcement-learning +2