Bin Wei

Bin Wei

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Bin Wei has a total of 62 co-authors. Here are the top co-authors by number of shared publications:

  • Yu Wang

    Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China

    2 shared publications
  • Bao Wang

    State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China

    1 shared publication
  • Chang Liu

    Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an 710072, China

    1 shared publication
  • Chen Zhang

    School of Ecology and Environment, Northwestern Polytechnical University, Xi’an 710072, China

    1 shared publication
  • Chenyao Li

    Key Laboratory of Industrial Fermentation Microbiology of Ministry of Education, Tianjin Industrial Microbiology Key Lab, College of Biotechnology of Tianjin University of Science and Technology, Tianjin, 300547, China

    1 shared publication
  • Chenzhou Zhang

    Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an 710072, China

    1 shared publication

Latest Publications

  • Open Access

    Comparative Transcriptome Profiling Analysis Uncovers Novel Heterosis-Related Candidate Genes Associated with Muscular Endurance in Mules

    by Shan Gao, Hojjat Asadollahpour Nanaei, Bin Wei, Yu Wang, Xihong Wang, Zongjun Li, Xuelei Dai, Zhichao Wang, Yu Jiang, Junjie Shao

    Heterosis has been widely exploited in animal and plant breeding programs to enhance the productive traits of hybrid progeny from two breeds or species. However, its underlying genetic mechanisms remain enigmatic. Transcriptome profiling analysis can be used as a method for exploring the mechanism of heterosis. Here, we performed genome-wide gene expression and alternative splicing (AS) analyses in different tissues (muscle, brain, and skin) from crosses between donkeys and horses. Our results indicated that 86.1% of the differentially expressed genes (DEGs) and 87.2% of the differential alternative splicing (DAS) genes showed over-dominance and dominance in muscle. Further analysis showed that the “muscle contraction” pathway was significantly enriched for both the DEGs and DAS genes in mule muscle tissue. Taken together, these DEGs and DAS genes could provide an index for future studies of the genetic and molecular mechanism of heterosis in the hybrids of donkey and horse.


  • Top Cited Papers

    Large-scale ruminant genome sequencing provides insights into their evolution and distinct traits

    by Lei Chen, Qiang Qiu, Yu Jiang, Kun Wang, Zeshan Lin, Zhipeng Li, Faysal Bibi, Yongzhi Yang, Jinhuan Wang, Wenhui Nie, et al.

    Phylogeny and characteristics of ruminants: Ruminants are a diverse group of mammals that includes families containing well-known taxa such as deer, cows, and goats. However, their evolutionary relationships have been contentious, as have the origins of their distinctive digestive systems and headgear, including antlers and horns (see the Perspective by Ker and Yang). To understand the relationships among ruminants, L. Chen et al. sequenced 44 species representing 6 families and performed a phylogenetic analysis. From this analysis, they were able to resolve the phylogeny of many genera and document incomplete lineage sorting among major clades. Interestingly, they found evidence for large population reductions among many taxa starting at approximately 100,000 years ago, coinciding with the migration of humans out of Africa. Examining the bony appendages on the head—the so-called headgear—Wang et al. describe specific evolutionary changes in the ruminants and identify selection on cancer-related genes that may function in antler development in deer. Finally, Lin et al. take a close look at the reindeer genome and identify the genetic basis of adaptations that allow reindeer to survive in the harsh conditions of the Arctic. Science , this issue p. eaav6202 , p. eaav6335 , p. eaav6312 ; see also p. 1130


  • Open Access

    Identification of a combination of SNPs associated with Graves’ disease using swarm intelligence

    by Bin Wei, QinKe Peng, QuanWei Zhang, ChenYao Li

    Graves’ disease, the production of thyroid-stimulating hormone receptor-stimulating antibodies leading to hyperthyroidism, is one of the most common forms of human autoimmune disease. It is widely agreed that complex diseases are not controlled simply by an individual gene or DNA variation but by their combination. Single nucleotide polymorphisms (SNPs), which are the most common form of DNA variation, have great potential as a medical diagnostic tool. In this paper, the P-value is used as a SNP pre-selection criterion, and a wrapper algorithm with binary particle swarm optimization is used to find the rule for discriminating between affected and control subjects. We analyzed the association between combinations of SNPs and Graves’ disease by investigating 108 SNPs in 384 cases and 652 controls. We evaluated our method by differentiating between cases and controls in a five-fold cross validation test, and it achieved a 72.9% prediction accuracy with a combination of 17 SNPs. The experimental results showed that SNPs, even those with a high P-value, have a greater effect on Graves’ disease when acting in a combination.