S. Gadagkar

Molecular Biology · 2005

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom S. Gadagkar trusts overall

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

  1. J. True
  2. Masatoshi Nei
  3. Koichiro Tamura
  4. W. Murphy
  5. Antonis Rokas
  6. Sudhir Kumar

Who trusts S. Gadagkar overall

  1. S. Edwards
  2. Laura Salter Kubatko
  3. James H. Degnan
  4. Diep Thi Hoang
  5. Olga Chernomor

Papers from S. Gadagkar's perspective

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

  1. Molecular phylogenetics and the origins of placental mammals (Nature)
  2. Genome-scale approaches to resolving incongruence in molecular phylogenies (Nature)
  3. Prospects for inferring very large phylogenies by using the neighbor-joining method. (Proceedings of the National Academy of Sciences of the United States of America)
  4. Estimation of divergence times from multiprotein sequences for a few mammalian species and several distantly related organisms (Proceedings of the National Academy of Sciences of the United States of America)
  5. Faculty Opinions recommendation of A molecular timescale of eukaryote evolution and the rise of complex multicellular life.
  6. Molecular systematics of armadillos (Xenarthra, Dasypodidae): contribution of maximum likelihood and Bayesian analyses of mitochondrial and nuclear genes. (Molecular Phylogenetics and Evolution)
  7. Evolutionary trees from DNA sequences: A maximum likelihood approach (Journal of Molecular Evolution)
  8. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.
  9. RAxML-III: a fast program for maximum likelihood-based inference of large phylogenetic trees (Bioinform.)
  10. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice.

Their papers