Isabelle Dupanloup

Genetics · 2002–2016

A researcher in the Science corpus: 5 papers; trusts 6 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

Whom Isabelle Dupanloup trusts overall

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

  1. Rasmus Nielsen
  2. J. Hey
  3. J. K. Pritchard
  4. Cristiano Varin
  5. Laurent Excoffier
  6. MARK A. Beaumont
  7. Hirotugu Akaike
  8. Matthew Stephens
  9. Heng Li
  10. Peter Beerli

Who trusts Isabelle Dupanloup overall

  1. Mark P. Miller
  2. Samuel A. Cushman
  3. Devon E. Pearse
  4. Laurent Excoffier
  5. I. Silva
  6. B. Swart
  7. Marianna Dixo
  8. Thibaut Jombart
  9. Roland Sánchez
  10. Andrew Storfer

Papers from Isabelle Dupanloup's perspective

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

  1. Inference of population structure using multilocus genotype data. (Genetics)
  2. Genetic history of an archaic hominin group from Denisova Cave in Siberia (Nature)
  3. Maximum likelihood estimation of a migration matrix and effective population sizes in n subpopulations by using a coalescent approach (Proceedings of the National Academy of Sciences of the United States of America)
  4. An Aboriginal Australian Genome Reveals Separate Human Dispersals into Asia (Science)
  5. Inferring human population size and separation history from multiple genome sequences (Nature Genetics)
  6. Inferring the Joint Demographic History of Multiple Populations from Multidimensional SNP Frequency Data (PLoS Genetics)
  7. Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics (Proceedings of the National Academy of Sciences of the United States of America)
  8. A new look at the statistical model identification
  9. Testing for ancient admixture between closely related populations. (Molecular biology and evolution)
  10. A map of human genome variation from population scale sequencing (Nature)

Their papers