This map shows the geographic impact of Di Ran's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Di Ran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Di Ran more than expected).
This network shows the impact of papers produced by Di Ran. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Di Ran. The network helps show where Di Ran may publish in the future.
Co-authorship network of co-authors of Di Ran
This figure shows the co-authorship network connecting the top 25 collaborators of Di Ran.
A scholar is included among the top collaborators of Di Ran based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Di Ran. Di Ran is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ran, Di, et al.. (2018). Research progress on neuroendocrinology controlling sheep seasonal reproduction.. 49(1). 18–25.1 indexed citations
8.
Liu, Qiuyue, Xiaofei Guo, Tao Feng, et al.. (2017). Establishment of high-throughput molecular detection methods for ovine high fecundity major gene FecB and their application.. 48(1). 39–51.10 indexed citations
9.
Huang, Dongwei, et al.. (2016). Expression analysis of DIO2 and DIO3 genes related to reproductive seasonality in goats (Capra hircus).. Journal of Pharmaceutical and Biomedical Sciences. 24(10). 1536–1543.2 indexed citations
10.
Yan, Yan, Pingqing Wang, Hao Geng, et al.. (2013). Polymorphism of AA-NAT gene and its relationship with litter size of Jining Grey goat of China. Animal Science Papers and Reports. 31(1). 15–26.6 indexed citations
11.
Ran, Di, et al.. (2011). DNA polymorphism of introns 1 and 2 of prolactin receptor gene and its association with litter size in goats.. Animal Science Papers and Reports. 29(4). 343–350.13 indexed citations
12.
Yan, Yan, Pingqing Wang, Di Ran, et al.. (2010). Steroid 21-hydroxylase gene (CYP21) as a candidate gene for prolificacy of Jining Grey goat.. Journal of Pharmaceutical and Biomedical Sciences. 18(5). 917–924.1 indexed citations
13.
Ran, Di, et al.. (2009). Polymorphism of gonadotropin releasing hormaone receptor (GnRHR) gene and its relationship with prolificacy of lining grey goat.. Journal of Pharmaceutical and Biomedical Sciences. 17(2). 218–223.3 indexed citations
14.
Feng, Tao, et al.. (2009). Cloning and sequence analysis on exons of neuropeptide Y gene in goats.. Anhui Nongye Daxue xuebao. 36(1). 128–132.1 indexed citations
15.
Wang, Pingqing, et al.. (2009). Polymorphism of Progesterone Receptor Gene and Its Relationship with Litter Size of Jining Grey Goats. Zhongguo nongye Kexue. 42(5). 1768–1775.1 indexed citations
16.
Feng, Tao, et al.. (2009). Polymorphism Analysis on Partial Exons of Estrogen Receptor (ESR) Gene in Goats. Journal of Pharmaceutical and Biomedical Sciences. 17(2). 237–242.1 indexed citations
17.
Ran, Di, et al.. (2009). Polymorphisms of TLR1 gene and their relationship with somatic cell score in Holstein cows.. Zhongguo nongye Kexue. 42(6). 2118–2125.2 indexed citations
18.
Zhang, Lin, Xuewei Li, Fang Li, et al.. (2009). Linkage Analysis between Microsatellite Locus LSCV043 and FecB Gene in Small Tail Han Sheep. Journal of Pharmaceutical and Biomedical Sciences. 17(4). 621–628.1 indexed citations
19.
Zhang, Baoyun, et al.. (2009). Polymorphic and linkage analysis of microsatellite OarJL36 and FecB gene in sheep.. Zhongguo nongye Kexue. 42(6). 2133–2141.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.