Lee-Shin Chu
Molecular Biology · 2022
A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 27 citations into it
- Computational Biology & Bioinformatics — 12 citations into it
- Radiology, Nuclear Medicine and Imaging — 6 citations into it
- Artificial Intelligence — 5 citations into it
Whom Lee-Shin Chu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Aroop Sircar
- Martin Steinegger
- Ratul Chowdhury
- Jeffrey J. Gray
- Jue Wang
- Nicholas A. Marze
- Brian L. Hie
- Joshua Meier
- James Dunbar
Who trusts Lee-Shin Chu overall
Papers from Lee-Shin Chu's perspective
Ordered by how strongly the researchers Lee-Shin Chu trusts endorse each paper. Same corpus, a different order for every researcher.
- Highly accurate protein structure prediction with AlphaFold
- Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences
- Attention is All you Need (Neural Information Processing Systems)
- Transformer protein language models are unsupervised structure learners
- The Rosetta all-atom energy function for macromolecular modeling and design
- Accurate prediction of protein structures and interactions using a 3-track neural network (Science)
- Language models enable zero-shot prediction of the effects of mutations on protein function
- Clustering huge protein sequence sets in linear time
- ProtTrans: Towards Cracking the Language of Life’s Code Through Self-Supervised Deep Learning and High Performance Computing
- 5分で分かる!? 有名論文ナナメ読み：Jacob Devlin et al. : BERT : Pre-training of Deep Bidirectional Transformers for Language Understanding