Lin Song

Molecular Biology · with Horvath · 2012

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Lin Song trusts overall

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

  1. Peter Langfelder
  2. Steve Horvath
  3. Atul J. Butte
  4. Patrick E. Meyer
  5. Ralph E. Steuer
  6. E. Ravasz
  7. Jeffrey D. Allen
  8. Adam A. Margolin
  9. Jeremiah J. Faith
  10. David N. Reshef

Papers from Lin Song's perspective

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

  1. Discovering functional relationships between RNA expression and chemotherapeutic susceptibility using relevance networks. (Proceedings of the National Academy of Sciences of the United States of America)
  2. Using Bayesian Networks to Analyze Expression Data (Annual International Conference on Research in Computational Molecular Biology)
  3. Information Theory: 1948-1998 - Guest Editorial
  4. ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context (BMC Bioinformatics)
  5. Hierarchical Organization of Modularity in Metabolic Networks (Science)
  6. Estimating mutual information using B-spline functions – an improved similarity measure for analysing gene expression data (BMC Bioinformatics)
  7. Large-Scale Mapping and Validation of Escherichia coli Transcriptional Regulation from a Compendium of Expression Profiles (PLoS Biology)
  8. Towards a Rigorous Assessment of Systems Biology Models: The DREAM3 Challenges (PLoS ONE)
  9. Gene connectivity, function, and sequence conservation: predictions from modular yeast co-expression networks (BMC Genomics)
  10. The mutual information: Detecting and evaluating dependencies between variables (European Conference on Computational Biology)

Their papers