Wei-Feng Shi

Prof. Wei-Feng Shi

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 June 2020 in Current Biology
Verified
Journal Article
Closed access
HZHong Zhou
Hong Zhou
XCXing Chen
Xing Chen
THTao Hu
Tao Hu
JLJuan Li
Juan Li
HSHao Song
Hao Song
WSWei-Feng Shi
Wei-Feng Shi

8 December 2021 in Nature
Verified
Journal Article
Closed access
PDF file
JLJuan Li
Juan Li
SLShengjie Lai
Shengjie Lai
GGGeorge F. Fu Gao
George F. Fu Gao
WSWei-Feng Shi
Wei-Feng Shi

1 August 2021 in Cell
Verified
Journal Article
Closed access
HZHong Zhou
Hong Zhou
JJJingkai Ji
Jingkai Ji
XCXing Chen
Xing Chen
YBYuhai Bi
Yuhai Bi
JLJuan Li
Juan Li
WSWei-Feng Shi
Wei-Feng Shi

1 December 2016 in Cell Host & Microbe
Verified
Journal Article
Closed access
YBYuhai Bi
Yuhai Bi
QCQuanjiao Chen
Quanjiao Chen
QWQianli Wang
Qianli Wang
JCJianjun Chen
Jianjun Chen
TJTao Jin
Tao Jin
GGGeorge F. Fu Gao
George F. Fu Gao

9 August 2010 in BMC Ecology and Evolution
Verified
Journal Article
Open access
PDF file
ALArong Luo
Arong Luo
HQHuijie Qiao
Huijie Qiao
YZYanzhou Zhang
Yanzhou Zhang
WSWei-Feng Shi
Wei-Feng Shi
SHSimon Yw Ho
Simon Yw Ho
CZChaodong Zhu
Chaodong Zhu
Background: Explicit evolutionary models are required in maximum-likelihood and Bayesian inference, the two methods that are overwhelmingly used in phylogenetic studies of DNA sequence data. Appropriate selection of nucleotide substitution models is important because the use of incorrect models can mislead phylogenetic inference. To better understand the performance of different model-selection criteria, we used 33,600 simulated data sets to analyse the accuracy, precision, dissimilarity, and biases of the hierarchical likelihood-ratio test, Akaike information criterion, Bayesian information criterion, and decision theory. Results: We demonstrate that the Bayesian information criterion and decision theory are the most appropriate model-selection criteria because of their high accuracy and precision. Our results also indicate that in some situations different models are selected by different criteria for the same dataset. Such dissimilarity was the highest between the hierarchical likelihood-ratio test and Akaike information criterion, and lowest between the Bayesian information criterion and decision theory. The hierarchical likelihood-ratio test performed poorly when the true model included a proportion of invariable sites, while the Bayesian information criterion and decision theory generally exhibited similar performance to each other. Conclusions: Our results indicate that the Bayesian information criterion and decision theory should be preferred for model selection. Together with model-adequacy tests, accurate model selection will serve to improve the reliability of phylogenetic inference and related analyses.

20 November 2020 in Nature Communications
Verified
Journal Article
Open access
PDF file
YBYuhai Bi
Yuhai Bi
JLJuan Li
Juan Li
SLShanqin Li
Shanqin Li
GFGuanghua Fu
Guanghua Fu
TJTao Jin
Tao Jin
WSWei-Feng Shi
Wei-Feng Shi
We have surveyed avian influenza virus (AIV) genomes from live poultry markets within China since 2014. Here we present a total of 16,091 samples that were collected from May 2016 to February 2019 in 23 provinces and municipalities in China. We identify 2048 AIV-positive samples and perform next generation sequencing. AIV-positive rates (12.73%) from samples had decreased substantially since 2016, compared to that during 2014–2016 (26.90%). Additionally, H9N2 has replaced H5N6 and H7N9 as the dominant AIV subtype in both chickens and ducks. Notably, novel reassortants and variants continually emerged and disseminated in avian populations, including H7N3, H9N9, H9N6 and H5N6 variants. Importantly, almost all of the H9 AIVs and many H7N9 and H6N2 strains prefer human-type receptors, posing an increased risk for human infections. In summary, our nation-wide surveillance highlights substantial changes in the circulation of AIVs since 2016, which greatly impacts the prevention and control of AIVs in China and worldwide.