Xuhua Xia

Molecular Biology · 2001–2018

A researcher in the Science corpus: 8 papers; trusts 12 researchers and is trusted by 37 researchers here, as inferred from the citation graph.

Subfields

Whom Xuhua Xia trusts overall

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

  1. Ivo L. Hofacker
  2. Marco Salemi
  3. Koichiro Tamura
  4. Z. Xie
  5. Richard Desper
  6. Julie Dawn Thompson
  7. Ziheng Yang
  8. Sudhir Kumar
  9. Anne-Mieke Vandamme
  10. Masatoshi Nei

Who trusts Xuhua Xia overall

  1. M. Heidemaa
  2. Z. Nagy
  3. Z. Xie
  4. M. Szarowska
  5. R. Lawson
  6. Feng-Chi Chen
  7. B. Glassey
  8. D. Guicking
  9. R. Barroso
  10. E. Onkendi

Papers from Xuhua Xia's perspective

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

  1. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice.
  2. DAMBE: software package for data analysis in molecular biology and evolution. (Journal of Heredity)
  3. Data Analysis in Molecular Biology and Evolution (Springer US)
  4. MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets. (Molecular biology and evolution)
  5. Vienna RNA secondary structure server (Nucleic Acids Res.)
  6. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. (Systematic Biology)
  7. Fast and Accurate Phylogeny Reconstruction Algorithms Based on the Minimum-Evolution Principle (Workshop on Algorithms in Bioinformatics)
  8. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.
  9. 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)
  10. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models

Their papers