Kai Feng

Molecular Biology · with Deng · 2017–2019

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

Whom Kai Feng trusts

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

  1. Steve Horvath (in Molecular Biology)
  2. Mark Newman (in Statistical and Nonlinear Physics)

Papers from Kai Feng's perspective

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

  1. Eigengene networks for studying the relationships between co-expression modules (BMC Systems Biology)
  2. A General Framework for Weighted Gene Co-Expression Network Analysis (Statistical Applications in Genetics and Molecular Biology)
  3. Geometric Interpretation of Gene Coexpression Network Analysis (PLoS Comput. Biol.)
  4. Reverse engineering gene networks using singular value decomposition and robust regression (Proceedings of the National Academy of Sciences of the United States of America)
  5. Finding community structure in networks using the eigenvectors of matrices. (Physical review. E, Statistical, nonlinear, and soft matter physics)
  6. R: A language and environment for statistical computing.
  7. Inferring Genetic Networks and Identifying Compound Mode of Action via Expression Profiling (Science)
  8. Network biology: understanding the cell's functional organization
  9. The modularity of pollination networks (Proceedings of the National Academy of Sciences of the United States of America)
  10. Microbial interactions: from networks to models (Nature Reviews Microbiology)

Their papers