Shanzhi Wang

Molecular Biology · 2010–2021

A researcher in the Science corpus: 3 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 65 citations into it
• Computational Theory and Mathematics — 26 citations into it
• Materials Chemistry — 11 citations into it
• Computational Chemistry & Drug Discovery — 6 citations into it

Whom Shanzhi Wang trusts overall

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

1. Marwin H. S. Segler

Papers from Shanzhi Wang's perspective

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

1. Dropout: a simple way to prevent neural networks from overfitting
2. A renaissance of neural networks in drug discovery
3. Deep Learning
4. Support-Vector Networks
5. Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks
6. Neural-Symbolic Machine Learning for Retrosynthesis and Reaction Prediction.
7. The rise of deep learning in drug discovery. (Drug Discovery Today)
8. Planning chemical syntheses with deep neural networks and symbolic AI
9. Protein-Ligand Scoring with Convolutional Neural Networks
10. Opportunities and obstacles for deep learning in biology and medicine

Their papers

• Gasdermin D in pyroptosis (2021) — 599 citations
• Machine Learning Methods in Drug Discovery (2020) — 324 citations
• Tyrosine Hydroxylase and Regulation of Dopamine Synthesis (2010) — 1,017 citations