Joseph K. Pickrell

Genetics · 2009–2019

A researcher in the Science corpus: 15 papers; trusts 20 researchers and is trusted by 49 researchers here, as inferred from the citation graph.

Subfields

Whom Joseph K. Pickrell trusts overall

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

  1. Daniel H. Huson
  2. David Reich
  3. J. K. Pritchard
  4. D. Steinberg
  5. Noah A. Rosenberg
  6. Nick Patterson
  7. ENCODEConsortium
  8. Daniel J. Lawson
  9. G. Nicholson
  10. S. Myers

Who trusts Joseph K. Pickrell overall

  1. Chris Wallace
  2. Torsten Günther
  3. Tomaz Berisa
  4. R. Fitak
  5. Gleb Kichaev
  6. Deren A. R. Eaton
  7. Edgar Dobriban
  8. Xiaowei Zhan
  9. Bogdan Pasaniuc
  10. Claudia R. Solís-Lemus

Papers from Joseph K. Pickrell's perspective

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

  1. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits (Proceedings of the National Academy of Sciences of the United States of America)
  2. Generating samples under a Wright-Fisher neutral model of genetic variation (Bioinform.)
  3. Supporting Online Material Materials and Methods Figs. S1 to S3 Tables S1 to S5 References Worldwide Human Relationships Inferred from Genome-wide Patterns of Variation
  4. SNPs in KCNQ1 are associated with susceptibility to type 2 diabetes in East Asian and European populations (Nature Genetics)
  5. Genotype, haplotype and copy-number variation in worldwide human populations (Nature)
  6. Defining the role of common variation in the genomic and biological architecture of adult human height
  7. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes (Nature Genetics)
  8. A Draft Sequence of the Neandertal Genome (Science)
  9. Common SNPs explain a large proportion of heritability for human height (Nature Genetics)
  10. Inference of Population Structure using Dense Haplotype Data

Their papers