Jing Li

Genetics · with Andrew · 2016

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jing Li trusts overall

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

  1. Heather J. Cordell
  2. Ryan J. Urbanowicz
  3. Casey S. Greene
  4. X. Chen
  5. Jeff Kiralis
  6. Purvesh Khatri
  7. Kathryn L. Lunetta
  8. Jason H. Moore
  9. Hemant Ishwaran
  10. Teri Manolio

Papers from Jing Li's perspective

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

  1. Detecting gene-gene interactions that underlie human diseases (Nature reviews genetics)
  2. Identifying SNPs predictive of phenotype using random forests (Genetic Epidemiology)
  3. Screening large-scale association study data: exploiting interactions using random forests
  4. Spatially Uniform ReliefF (SURF) for computationally-efficient filtering of gene-gene interactions
  5. GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures
  6. A random forest approach to the detection of epistatic interactions in case-control studies (BMC Bioinformatics)
  7. Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection
  8. Genome-wide association studies for common diseases and complex traits (Nature reviews genetics)
  9. Understanding multicellular function and disease with human tissue-specific networks
  10. A balanced accuracy function for epistasis modeling in imbalanced datasets using multifactor dimensionality reduction (Genetic Epidemiology)

Their papers