Luhua Lai

Molecular Biology · 1997–2022

A researcher in the Science corpus: 16 papers; trusts 4 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 132 citations into it; #2,701 of 17,773 by trust here, #3,389 by citations
• Computational Theory and Mathematics — 94 citations into it; #2,934 of 12,182 by trust here, #553 by citations
• Computational Chemistry & Drug Discovery — 50 citations into it; #106 of 425 by trust here, #159 by citations
• Pharmacology — 19 citations into it; #109 of 1,112 by trust here, #106 by citations

Whom Luhua Lai trusts overall

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

1. Geoffrey E. Hinton
2. Daniel Quang
3. Babak Alipanahi

Who trusts Luhua Lai overall

1. Shengyou Huang
2. Pedro J. Ballester
3. R. Quiroga
4. Gregory Sliwoski
5. Kun-Yi Hsin
6. Sérgio Filipe Sousa
7. Shiwei Wang
8. Jocelyn Sunseri
9. Nicolas Moitessier
10. Xiaoqin Zou

Papers from Luhua Lai's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. ImageNet: A large-scale hierarchical image database

Their papers

• Deep Learning for Drug-Induced Liver Injury (2015) — 324 citations
• Further development and validation of empirical scoring functions for structure-based binding affinity prediction (2002) — 1,084 citations
• Nonnatural protein–protein interaction-pair design by key residues grafting (2007) — 86 citations
• LigBuilder: A Multi-Purpose Program for Structure-Based Drug Design (2000) — 282 citations
• Computation of Octanol-Water Partition Coefficients by Guiding an Additive Model with Knowledge (2007) — 780 citations
• Transfer Learning for Drug Discovery. (2020) — 307 citations
• Binding site detection and druggability prediction of protein targets for structure-based drug design. (2013) — 172 citations
• CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction (2018) — 342 citations
• Sequence-based prediction of protein protein interaction using a deep-learning algorithm (2017) — 341 citations
• Structure-based de novo drug design using 3D deep generative models (2021) — 150 citations
• CavitySpace: A Database of Potential Ligand Binding Sites in the Human Proteome (2022) — 29 citations
• De Novo Design of Multitarget Ligands with an Iterative Fragment-Growing Strategy (2014) — 54 citations
• PharmMapper 2017 update: a web server for potential drug target identification with a comprehensive target pharmacophore database (2017) — 1,362 citations
• Computational design of ligand-binding proteins. (2017) — 53 citations
• A protein engineered to bind uranyl selectively and with femtomolar affinity. (2014) — 309 citations
• A New Atom-Additive Method for Calculating Partition Coefficients (1997)