Xiaoying Lan

1.0k citations
20 papers · 708 · h-index 15

Impact in

  • Hematology top 10%
    • Chronic Myeloid Leukemia Treatments
  • Oncology top 10%
    • Peptidase Inhibition and Analysis
    • Cancer-related Molecular Pathways

Papers in

    • Ubiquitin and proteasome pathways 6
    • Cell death mechanisms and regulation 2
    • Chronic Myeloid Leukemia Treatments 4

Xiaoying Lan

18 papers receiving 702 citations

Peers

Xiaoying Lan
Comparison fields: 5 of 69
  • Hematology 92
  • Oncology 205
  • Molecular Biology 423
  • Cancer Research 63
  • Cell Biology 59
Replace Jyoti Kanwar with:
Jyoti Kanwar India
Changshan Yang China
Clara Lemos Netherlands
Haolan Wang China
Xianping Shi China
Karin von Schwarzenberg Germany
Dan Zang China
Zi‐Ren Zhou China
Daniela Buac United States
Sarah Mackenzie United States
Xiaoying Lan relative to Jyoti Kanwar India Jyoti Kanwar's profile →
Citations per field
00.5×1.5×
Jyoti Kanwar · 1×
Citations per year

Countries citing papers authored by Xiaoying Lan

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoying Lan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiaoying Lan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xiaoying Lan Line = papers co-authored together Xiaoying Lan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2013115
2 201471
3 201470
4 201767
5 201559
6 201652
7 201439
8 201636
9 201935
10 201731
11 201731
12 201626
13 201523
14 201621
15 201719
16 20207
17 20225
18 20211
19 20250
20 20230

About Xiaoying Lan

Xiaoying Lan is a scholar working on Molecular Biology, Hematology, Oncology, Cell Biology and Plant Science, having authored 20 papers that have together received 708 indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (6 papers), Chronic Myeloid Leukemia Treatments (4 papers), Endoplasmic Reticulum Stress and Disease (3 papers), Peptidase Inhibition and Analysis (3 papers), Cell death mechanisms and regulation (2 papers), Natural Compound Pharmacology Studies (2 papers), Autophagy in Disease and Therapy (2 papers) and Eosinophilic Disorders and Syndromes (2 papers). The work is most often cited by research in Hematology (92 citations), Oncology (205 citations), Molecular Biology (423 citations), Cancer Research (63 citations) and Cell Biology (59 citations). Xiaoying Lan has collaborated with scholars based in China and United States. Frequent co-authors include Hongbiao Huang, Jinbao Liu, Xianping Shi, Xuejun Wang, Xin Chen, Chong Zhao, Ningning Liu, Q. Ping Dou, Shouting Liu and Dan Zang. Their work appears in journals such as Oncotarget, Cell Death and Disease, Scientific Reports, Biochemical Pharmacology and Clinical Cancer Research.

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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