Chenran Wang

Molecular Biology · 2019

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 39 citations into it
• Materials Chemistry — 19 citations into it

Whom Chenran Wang trusts overall

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

1. I. Samish

Papers from Chenran Wang's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Learning
3. Native protein sequences are close to optimal for their structures.
4. De Novo Computational Design of Retro-Aldol Enzymes
5. The Stanford CoreNLP Natural Language Processing Toolkit
6. A large scale test of computational protein design: folding and stability of nine completely redesigned globular proteins.
7. De novo design of the hydrophobic cores of proteins
8. Computational design of an enzyme catalyst for a stereoselective bimolecular Diels-Alder reaction
9. Molecular technology: Designing proteins and peptides
10. Computational Thermostabilization of an Enzyme

Their papers

• ProDCoNN: Protein design using a convolutional neural network (2019) — 71 citations