Li Haipeng

Biography

Professor Li Haipeng graduated from Kunming Institute of Zoology, Chinese Academy of Sciences with a PhD degree in 2002. Later, he pursued his research in theoretical population genetics as a research fellow at University of Texas at Houston, USA, and as a postdoctoral fellow at University of Munich, Germany and University of Cologne, Germany. In 2007, he was accepted by CAS-MPG Partner Institute for Computational Biology, CAS as a professor, a principle investigator and a PhD supervisor. Professor Li Haipeng devoted his efforts to the improvement of methods to detect recent positive selection in the past 20 years. 1) He used the information of phylogenetic (or coalescent) tree to detect recent positive selection and proved mathematically that the statistical test is free from the confounding impacts of demography. Notably, This goal is first achieved in population genetics. 2) To avoid the confounding signatures of recombination, a very fast method was proposed to estimate recombination rate based on population-genetic data.The new method is as precise as the popularly used LDhat, and it is more than 100,000 times faster than LDhat. 3) A novel method has been proposed to detect recent positive selection, conditional on the demographic parameters inferred from the genome-wide DNA polymorphism pattern. The utmost goals in the future would be to develop the new methods that are free from the confounding impacts of demography and recombination, and suitable for the genome-wide DNA polymorphism data set. It will definitely promote the study on the mechanism of adaptation and enlighten us about how natural selection has accelerated the emergence of consciousness and language.

Research Interest

Professor Li Haipeng group works in the field of population genetics and bioinformatics. With regard to population genetics, our goals are to study the mechanism of recent adaptation due to positive selection in living organisms, such as humans, Drosophila and pathogens. We search for methods to detect selection which are not influenced by a high false positive rate because of the confounding impact of demography (i.e., varying population size and population structure) and genetic recombination. Our research activities can help us to understand the function of genes and the interaction between genes and environment. We are studying how natural selection has helped humans to adapt to environmental changes and especially how natural selection has accelerated the emergence of consciousness and language. In the field of bioinformatics, we develop comprehensive software to meet various needs in genetic data