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Center for Computational and Evolutionary Biology

Center for Computational and Evolutionary Biology (CCEB) is established to foster interactions and collaborations between biologists and mathematicians, statisticians, and computer scientists.  It is a virtual center based in the Institute of Zoology, Chinese Academy of Sciences, Beijing.  The Center is cross-institutional and inter-disciplinary.  We invite both mathematicians who are interested in developing statistical methods and computational algorithms for analysis of biological data and biologists who may benefit from such methods to join in and become members of the center.

The main motivation for the establishment of the Center is the perception that very few theoreticians are developing methods of genetic data analysis in China, even though Chinese experimental biologists are very experienced at generating large quantities of data.  Traditionally subject areas such as population genetics, molecular evolution, and molecular phylogenetics have made extensive use of probability and statistics, many times driving the development or novel methodologies and algorithms in computational statistics.  The rapid accumulation of genetic data in the genomic era has made the need for methodological studies even more acute.

The Center will cover all subject areas where statistical methods and computational algorithms are applied to analyze genetic and genomic data. Examples include sequence analysis (pattern matching, similarity search, molecular evolution, molecular phylogenetics and population genetics), inference of gene/protein interaction networks, association studies to identify disease genes, etc.  We emphasize statistical properties of analytical methods in addition to computational speed, and encourage work that involves probabilistic modelling.

The Center will initially be virtual.  In the long run, we expect to make a few permanent appointments in the Center if/when suitable candidates can be identified.  An important function of the Center is to organize seminars, discussion meetings and workshops.

Scientists in the Beijing area with relevant interests are invited to join the Center to become associate members.

Publications from the Center:

  • Zhang C, Zhang D-X, Zhu T, Yang Z (2011) Evaluation of a Bayesian coalescent method of species delimitation. Syst Biol: in press.
  • dos Reis M, Yang Z (2011) Approximate likelihood calculation for Bayesian estimation of divergence times. Mol Biol Evol 28:2161­2172.
  • Groussin M, Pawlowski J, Yang Z (2011) Bayesian relaxed clock estimation of divergence times in Foraminifera. Mol Phylogenet Evol 61:157-166.
  • Leng L, Zhang DX  (2011) Measuring population differentiation using GST or D? A simulation study with microsatellite DNA markers under a finite island model. Mol Ecol 20:2494-2509.
  • Yang Z, dos Reis M (2011) Statistical properties of the branch-site test of positive selection. Mol Biol Evol 28:1217-1228.
  • Zhu T, Hu Y, Ma Z, Zhang D-X, Li T, Yang Z (2011) Efficient simulation under a population genetics model of carcinogenesis. Bioinformatics 27:837-843.
  • Huang ZS, Zhang DX (2010) CVhaplot: a consensus tool for statistical haplotyping. Mol Ecol Resour 10:1066–1070.
  • Yang Z, Rannala B (2010) Bayesian species delimitation using multilocus sequence data. Proc Natl Acad Sci USA 107:9264-9269.
  • Huang ZS, Ji YJ, Zhang DX (2009) Internal algorithm variability and among-algorithm discordance in statistical haplotype reconstruction. Mol Ecol 18:1556-1559.
  • Zhang DX, Yan LN, Ji YJ, Hewitt GM, Huang ZS (2009) Unexpected relationships of substructured populations in Chinese Locusta migratoria. BMC Evol Biol 9:144. doi:10.1186/1471-2148-9-144.
  • Huang ZS,Ji YJ,Zhang DX (2008) Haplotype reconstruction for scnp DNA: a consensus vote approach with extensive sequence data from populations of the migratory locust (Locusta migratoria). Mol Ecol 17:1930-1947.


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