Jun Wang

Molecular Biology · with Kaneko · 2022

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jun Wang trusts overall

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

  1. Mark Newman
  2. W. Kabsch

Papers from Jun Wang's perspective

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

  1. Mixing patterns in networks. (Physical review. E, Statistical, nonlinear, and soft matter physics)
  2. Modularity from fluctuations in random graphs and complex networks. (Physical review. E, Statistical, nonlinear, and soft matter physics)
  3. Specificity and Stability in Topology of Protein Networks (Science)
  4. Assortative mixing in networks. (Physical Review Letters)
  5. Fast unfolding of communities in large networks
  6. Fast algorithm for detecting community structure in networks.
  7. Improved protein structure prediction using potentials from deep learning
  8. Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features
  9. A series of PDB related databases for everyday needs
  10. AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models

Their papers