Qing Yan Liu

1.2k total citations
30 papers, 871 citations indexed

About

Qing Yan Liu is a scholar working on Molecular Biology, Physiology and Oncology. According to data from OpenAlex, Qing Yan Liu has authored 30 papers receiving a total of 871 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 7 papers in Physiology and 6 papers in Oncology. Recurrent topics in Qing Yan Liu's work include Alzheimer's disease research and treatments (7 papers), Drug Transport and Resistance Mechanisms (4 papers) and Glycosylation and Glycoproteins Research (3 papers). Qing Yan Liu is often cited by papers focused on Alzheimer's disease research and treatments (7 papers), Drug Transport and Resistance Mechanisms (4 papers) and Glycosylation and Glycoproteins Research (3 papers). Qing Yan Liu collaborates with scholars based in Canada, United States and China. Qing Yan Liu's co-authors include Wandong Zhang, Danica Stanimirovic, Michael Reith, Douglas G. Walker, Lih‐Fen Lue, Debbie Callaghan, Ignacio A. Romero, Babette B. Weksler, Ziying Liu and Ze Yang and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Blood.

In The Last Decade

Qing Yan Liu

30 papers receiving 846 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Qing Yan Liu Canada 15 358 324 216 103 71 30 871
Chunyun Liu China 17 241 0.7× 178 0.5× 253 1.2× 168 1.6× 85 1.2× 44 847
Huifang Sun China 14 400 1.1× 153 0.5× 63 0.3× 82 0.8× 21 0.3× 44 838
Akinori Miyashita Japan 24 865 2.4× 620 1.9× 169 0.8× 158 1.5× 21 0.3× 70 1.6k
H Mar United States 8 555 1.6× 526 1.6× 102 0.5× 82 0.8× 24 0.3× 11 898
D.R. Rosen United States 16 605 1.7× 198 0.6× 154 0.7× 236 2.3× 29 0.4× 34 1.2k
Paola Lorenzon Italy 19 728 2.0× 163 0.5× 43 0.2× 284 2.8× 16 0.2× 62 1.2k
Konstantin Glebov Germany 15 460 1.3× 314 1.0× 306 1.4× 146 1.4× 19 0.3× 17 937
K. Ishiguro Japan 11 509 1.4× 374 1.2× 50 0.2× 191 1.9× 48 0.7× 17 943
Viyada Nunbhakdi‐Craig United States 12 1.0k 2.9× 545 1.7× 237 1.1× 236 2.3× 24 0.3× 12 1.7k

Countries citing papers authored by Qing Yan Liu

Since Specialization
Citations

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

Fields of papers citing papers by Qing Yan Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qing Yan Liu

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

All Works

20 of 20 papers shown
1.
Zhang, Wandong, Qing Yan Liu, Arsalan S. Haqqani, et al.. (2023). Differential Expression of ABC Transporter Genes in Brain Vessels vs. Peripheral Tissues and Vessels from Human, Mouse and Rat. Pharmaceutics. 15(5). 1563–1563. 15 indexed citations
2.
Freitas‐Andrade, Moises, César H. Comin, Peter Van Dyken, et al.. (2023). Astroglial Hmgb1 regulates postnatal astrocyte morphogenesis and cerebrovascular maturation. Nature Communications. 14(1). 4965–4965. 14 indexed citations
3.
Liu, Qing Yan, Sonia Leclerc, Youlian Pan, et al.. (2021). Novel Transcriptional and Translational Biomarkers of Tularemia Vaccine Efficacy in a Mouse Inhalation Model: Proof of Concept. Microorganisms. 10(1). 36–36. 1 indexed citations
4.
Zhang, Wandong, Qing Yan Liu, Arsalan S. Haqqani, et al.. (2020). Differential expression of receptors mediating receptor-mediated transcytosis (RMT) in brain microvessels, brain parenchyma and peripheral tissues of the mouse and the human. Fluids and Barriers of the CNS. 17(1). 47–47. 126 indexed citations
5.
Liu, Xin, et al.. (2016). Automatic annotation and visualization tool for mass spectrometry based glycomics. Rapid Communications in Mass Spectrometry. 30(23). 2471–2479. 5 indexed citations
6.
Liu, Qing Yan, et al.. (2014). Apolipoprotein E, amyloid-beta, and neuroinflammation in Alzheimer’s disease. Neuroscience Bulletin. 30(2). 317–330. 80 indexed citations
7.
Zhang, Hongquan, Zhaohui Wang, Jacek Stupak, et al.. (2012). Targeted glycomics by selected reaction monitoring for highly sensitive glycan compositional analysis. PROTEOMICS. 12(15-16). 2510–2522. 16 indexed citations
8.
9.
Liu, Xin, et al.. (2012). Improve accuracy and sensibility in glycan structure prediction by matching glycan isotope abundance. Analytica Chimica Acta. 743. 80–89. 7 indexed citations
10.
Liu, Qing Yan, et al.. (2011). The Comparison between the Borate Glass Ceramic Porous Scaffolds Preparing by the Sintering and Binding Method. Materials science forum. 675-677. 321–324. 1 indexed citations
11.
Liu, Rugao, Joy X Lei, Chun Luo, et al.. (2011). Increased EID1 nuclear translocation impairs synaptic plasticity and memory function associated with pathogenesis of Alzheimer's disease. Neurobiology of Disease. 45(3). 902–912. 32 indexed citations
12.
Callaghan, Debbie, Douglas G. Walker, Lih‐Fen Lue, et al.. (2009). Expression of inflammatory genes induced by beta-amyloid peptides in human brain endothelial cells and in Alzheimer's brain is mediated by the JNK-AP1 signaling pathway. Neurobiology of Disease. 34(1). 95–106. 185 indexed citations
13.
Partis, Lina, Malcolm Burns, Koichi Chiba, et al.. (2007). A study of comparability in amplified fragment length polymorphism profiling using a simple model system. Electrophoresis. 28(18). 3193–3200. 4 indexed citations
14.
Gan, Li, et al.. (2007). Neurogenic responses to amyloid-beta plaques in the brain of Alzheimer’s disease-like transgenic (pPDGF-APPSw,Ind) mice. Neurobiology of Disease. 29(1). 71–80. 63 indexed citations
15.
16.
Walker, P. Roy, Brandon Smith, Qing Yan Liu, et al.. (2004). Data mining of gene expression changes in Alzheimer brain. Artificial Intelligence in Medicine. 31(2). 137–154. 51 indexed citations
17.
Liu, Qing Yan, et al.. (2000). Effects of neoplastic transformation and teniposide (VM26) on protein kinase C isoform expression in rodent fibroblasts. Cancer Letters. 153(1-2). 13–23. 3 indexed citations
18.
Liu, Qing Yan, Sandra L. Baldauf, & Michael Reith. (1996). Elongation factor 1? genes of the red alga Porphyra purpurea include a novel, developmentally specialized variant. Plant Molecular Biology. 31(1). 77–85. 21 indexed citations
19.
Liu, Qing Yan & Michael Reith. (1996). A SPOROPHYTE CELL WALL PROTEIN OF THE RED ALGA PORPHYRA PURPUREA (RHODOPHYTA) IS A NOVEL MEMBER OF THE CHYMOTRYPSIN FAMILY OF SERINE PROTEASES1. Journal of Phycology. 32(6). 1003–1009. 8 indexed citations
20.
Bird, C. J., E. L. Rice, Colleen Murphy, Qing Yan Liu, & Mark A. Ragan. (1990). Nucleotide sequences of 18S ribosomal RNA genes from the red algaeGracilaria tikvahiaeMcLachlan,Gracilaria verrucosa(Hudson) Papenfuss andGracilariopsissp.. Nucleic Acids Research. 18(13). 4023–4023. 32 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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