Jue Wang
Molecular Biology · with Baker · 2020–2026
A researcher in the Science corpus: 9 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 197 citations into it
Whom Jue Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- S. Parasuraman
- M. Bootman
- Ivan V. Anishchenko
- Raymond A. Yeh
- David Baker
- Namrata Anand
- Christoffer H Norn
- Surojit Biswas
- K. Simons
- Sergey Ovchinnikov
Who trusts Jue Wang overall
- Jeffrey A. Ruffolo
- Brian L. Trippe
- Kevin Kaichuang Yang
- Lee-Shin Chu
- Casper A. Goverde
- Ivan V. Anishchenko
- Luhuan Wu
Papers from Jue Wang's perspective
Ordered by how strongly the researchers Jue Wang trusts endorse each paper. Same corpus, a different order for every researcher.
- 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
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Denoising Diffusion Probabilistic Models (Neural Information Processing Systems)
- Computational design of an enzyme catalyst for a stereoselective bimolecular Diels-Alder reaction
- ImageNet classification with deep convolutional neural networks
- Highly accurate protein structure prediction for the human proteome
- A Connection Between Score Matching and Denoising Autoencoders
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Deep learning methods for designing proteins scaffolding functional sites (2021) — 38 citations
- Scaffolding protein functional sites using deep learning (2022) — 414 citations
- Design of proteins presenting discontinuous functional sites using deep learning (2020) — 40 citations
- Broadly applicable and accurate protein design by integrating structure prediction networks and diffusion generative models (2022) — 200 citations
- De novo design of protein structure and function with RFdiffusion (2023) — 1,299 citations
- Generalized Biomolecular Modeling and Design with RoseTTAFold All-Atom (2023) — 924 citations
- Conductance stable and mechanically durable bi-layer EGaIn composite-coated stretchable fiber for 1D bioelectronics (2023) — 599 citations
- Paclitaxel drives TREM2+ macrophage expansion underlying its inferior therapeutic efficacy compared to Nab-paclitaxel (2026) — 735 citations
- RoseTTAFold: The first release of RoseTTAFold (2021)