Yuedong Yang

Molecular Biology · 2010–2022

A researcher in the Science corpus: 22 papers; trusts 116 researchers and is trusted by 50 researchers here, as inferred from the citation graph.

Subfields

Molecular Biology — 355 citations into it; #687 of 17,773 by trust here, #1,563 by citations
Materials Chemistry — 200 citations into it; #632 of 11,513 by trust here, #2,564 by citations
Computational Biology & Bioinformatics — 139 citations into it; #448 of 660 by trust here, #432 by citations
Artificial Intelligence — 86 citations into it
Computational Theory and Mathematics — 65 citations into it; #4,782 of 12,182 by trust here, #1,587 by citations
Model Architectures — 62 citations into it
Computer Vision and Pattern Recognition — 60 citations into it
Spectroscopy — 43 citations into it

Whom Yuedong Yang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

Who trusts Yuedong Yang overall

Papers from Yuedong Yang's perspective

Ordered by how strongly the researchers Yuedong Yang trusts endorse each paper. Same corpus, a different order for every researcher.

ImageNet classification with deep convolutional neural networks
Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
Long Short-Term Memory
Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
Attention is All you Need (Neural Information Processing Systems)
Gradient-based learning applied to document recognition
ImageNet: A large-scale hierarchical image database
Learning Multiple Layers of Features from Tiny Images
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Going deeper with convolutions

Their papers

Improving protein fold recognition and template-based modeling by employing probabilistic-based matching between predicted one-dimensional structural properties of query and corresponding native properties of templates (2011) — 321 citations
Capturing non‐local interactions by long short‐term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility (2017) — 329 citations
SPINE X: Improving protein secondary structure prediction by multi-step learning coupled with prediction of solvent accessible surface area and backbone torsion angles (2011) — 258 citations
Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto‐encoder deep neural network (2014) — 152 citations
Energy functions in de novo protein design: current challenges and future prospects. (2013) — 78 citations
Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning (2015) — 346 citations
Accurate prediction of protein contact maps by coupling residual two-dimensional bidirectional long short-term memory with convolutional neural networks (2018) — 158 citations
SPIDER2: A Package to Predict Secondary Structure, Accessible Surface Area, and Main-Chain Torsional Angles by Deep Neural Networks. (2017) — 149 citations
Sixty-five years of the long march in protein secondary structure prediction: the final stretch? (2016) — 235 citations
Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins (2016) — 99 citations
Direct prediction of profiles of sequences compatible with a protein structure by neural networks with fragment‐based local and energy‐based nonlocal profiles (2014) — 84 citations
SPIN2: Predicting sequence profiles from protein structures using deep neural networks (2018) — 101 citations
Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of recurrent and residual convolutional neural networks (2018) — 171 citations
Improving computational protein design by using structure-derived sequence profile (2010) — 25 citations
Detecting Proline and Non-Proline Cis Isomers in Protein Structures from Sequences Using Deep Residual Ensemble Learning (2018) — 14 citations
Improving protein disorder prediction by deep bidirectional long short‐term memory recurrent neural networks (2016) — 250 citations
Structure-Aware Multimodal Deep Learning for Drug-Protein Interaction Prediction (2022) — 65 citations
AlphaFold2-aware protein-DNA binding site prediction using graph transformer (2022) — 109 citations
Predicting drug–protein interaction using quasi-visual question answering system (2019) — 291 citations
To Improve Protein Sequence Profile Prediction through Image Captioning on Pairwise Residue Distance Map (2019) — 61 citations