Hailong Yan

3.0k total citations
63 papers, 2.2k citations indexed

About

Hailong Yan is a scholar working on Genetics, Molecular Biology and Cancer Research. According to data from OpenAlex, Hailong Yan has authored 63 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Genetics, 27 papers in Molecular Biology and 11 papers in Cancer Research. Recurrent topics in Hailong Yan's work include Genetic and phenotypic traits in livestock (21 papers), Animal Genetics and Reproduction (13 papers) and Cancer-related molecular mechanisms research (11 papers). Hailong Yan is often cited by papers focused on Genetic and phenotypic traits in livestock (21 papers), Animal Genetics and Reproduction (13 papers) and Cancer-related molecular mechanisms research (11 papers). Hailong Yan collaborates with scholars based in China, United States and Australia. Hailong Yan's co-authors include Lei Qu, Haijing Zhu, Chuanying Pan, Ke Wang, Lanqun Mao, Ping Yu, Huibiao Liu, Xianyong Lan, Yuliang Li and Yulin Chen and has published in prestigious journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Hailong Yan

62 papers receiving 2.2k citations

Peers

Hailong Yan

GENET

ACS

Linjie Wang China

Miaomiao Li China

Ruijia Wang China

Xiangqian Zhang China

Yao Xiao China

Honghua Li China

Yonghua Sun China

Yingying Han China

Miaomiao Zhang China

Kan Liu China

Linjie Wang China

Hailong Yan

426 ×0.4

GENET

1.1k ×1.3

552 ×1.4

241 ×0.9

104 ×0.4

ACS

Citations per year, relative to Hailong Yan Hailong Yan (= 1×) peers Linjie Wang

Countries citing papers authored by Hailong Yan

Since Specialization

Citations

This map shows the geographic impact of Hailong Yan'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 Hailong Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hailong Yan more than expected).

Fields of papers citing papers by Hailong Yan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hailong Yan. 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 Hailong Yan. The network helps show where Hailong Yan may publish in the future.

Co-authorship network of co-authors of Hailong Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Hailong Yan. A scholar is included among the top collaborators of Hailong Yan 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 Hailong Yan. Hailong Yan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Yan, Hailong, et al.. (2023). Folate-mediated one-carbon metabolism as a potential antifungal target for the sustainable cultivation of microalga Haematococcus pluvialis. SHILAP Revista de lepidopterología. 16(1). 104–104. 7 indexed citations

Yan, Hailong, Yan Li, Ye Gao, et al.. (2022). miR-1 Regulates Differentiation and Proliferation of Goat Hair Follicle Stem Cells by Targeting IGF1R and LEF1 Genes. DNA and Cell Biology. 41(2). 190–201. 4 indexed citations

Yan, Hailong, Haiyan Ma, Yanhua Li, et al.. (2022). Oxidative stress facilitates infection of the unicellular alga Haematococcus pluvialis by the fungus Paraphysoderma sedebokerense. SHILAP Revista de lepidopterología. 15(1). 56–56. 5 indexed citations

Chen, Yi, et al.. (2020). High-throughput fluorescence-activated cell sorting for cell wall-deficient microalgal mutants screening. Algal Research. 50. 102011–102011. 18 indexed citations

Wang, Ke, Zihong Kang, Enhui Jiang, et al.. (2020). Genetic effects of DSCAML1 identified in genome-wide association study revealing strong associations with litter size and semen quality in goat (Capra hircus). Theriogenology. 146. 20–25. 63 indexed citations

Kang, Zihong, Enhui Jiang, Ke Wang, et al.. (2019). Goat membrane associated ring-CH-type finger 1 (MARCH1) mRNA expression and association with litter size. Theriogenology. 128. 8–16. 51 indexed citations

Yan, Hailong, Ke Wang, Yang Cui, et al.. (2019). Goat SPEF2: Expression profile, indel variants identification and association analysis with litter size. Theriogenology. 139. 147–155. 37 indexed citations

Yan, Hailong, Ye Gao, Qiang Ding, et al.. (2019). Exosomal Micro RNAs Derived from Dermal Papilla Cells Mediate Hair Follicle Stem Cell Proliferation and Differentiation. International Journal of Biological Sciences. 15(7). 1368–1382. 79 indexed citations

Zhang, Yanghai, Wenbo Cui, Min Wang, et al.. (2019). A novel missense mutation (L280V) within POU1F1 gene strongly affects litter size and growth traits in goat. Theriogenology. 135. 198–203. 27 indexed citations

10.

Zhang, Xiaoyan, Shuai Yu, Qing Yang, et al.. (2018). Goat Boule: Isoforms identification, mRNA expression in testis and functional study and promoter methylation profiles. Theriogenology. 116. 53–63. 5 indexed citations

11.

Wang, Ke, Hailong Yan, Haijing Zhu, et al.. (2018). Detection of insertion/deletions (indels) of the <i>ATBF1</i> gene and their effects on growth-related traits in three indigenous goat breeds. Archives animal breeding/Archiv für Tierzucht. 61(3). 311–319. 3 indexed citations

12.

Wang, Ke, Hailong Yan, Han Xu, et al.. (2018). A novel indel within goat casein alpha S1 gene is significantly associated with litter size. Gene. 671. 161–169. 58 indexed citations

13.

Zhang, Xuelian, Hailong Yan, Ke Wang, et al.. (2018). Goat CTNNB1: mRNA expression profile of alternative splicing in testis and association analysis with litter size. Gene. 679. 297–304. 28 indexed citations

14.

Shi, Bingbo, Qiang Ding, Xiaolin He, et al.. (2016). Tβ4-overexpression based on the piggyBac transposon system in cashmere goats alters hair fiber characteristics. Transgenic Research. 26(1). 77–85. 17 indexed citations

15.

Yan, Hailong, Dan Chen, Yifan Wang, et al.. (2016). Ribosomal protein L18aB is required for both male gametophyte function and embryo development in Arabidopsis. Scientific Reports. 6(1). 31195–31195. 35 indexed citations

16.

Wang, Xiaolong, Bei Cai, Jiankui Zhou, et al.. (2016). Disruption of FGF5 in Cashmere Goats Using CRISPR/Cas9 Results in More Secondary Hair Follicles and Longer Fibers. PLoS ONE. 11(10). e0164640–e0164640. 67 indexed citations

17.

Wang, Xiaolong, Jing Liu, Guangxian Zhou, et al.. (2016). Whole-genome sequencing of eight goat populations for the detection of selection signatures underlying production and adaptive traits. Scientific Reports. 6(1). 38932–38932. 109 indexed citations

18.

Wang, Xiaolong, Yiyuan Niu, Jiankui Zhou, et al.. (2016). Multiplex gene editing via CRISPR/Cas9 exhibits desirable muscle hypertrophy without detectable off-target effects in sheep. Scientific Reports. 6(1). 32271–32271. 74 indexed citations

19.

Gao, Ye, Xiaolong Wang, Hailong Yan, et al.. (2016). Comparative Transcriptome Analysis of Fetal Skin Reveals Key Genes Related to Hair Follicle Morphogenesis in Cashmere Goats. PLoS ONE. 11(3). e0151118–e0151118. 74 indexed citations

20.

Zeng, Fuxing, Hailong Yan, & Stefan K. Arndt. (2009). Leaf and whole tree adaptations to mild salinity in field grown Populus euphratica. Tree Physiology. 29(10). 1237–1246. 33 indexed citations

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.

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