X.‐L. Wu

445 citations
8 papers · 349 · h-index 6

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • Genetic and phenotypic traits in livestock
    • Genetic Mapping and Diversity in Plants and Animals

Papers in

    • Genetic and phenotypic traits in livestock 6
    • Genetic Mapping and Diversity in Plants and Animals 6
    • Livestock Farming and Management 1

X.‐L. Wu

8 papers receiving 343 citations

Peers

X.‐L. Wu
Comparison fields: 5 of 50
  • Cancer Research 89
  • Genetics 163
  • Hematology 35
  • Plant Science 88
  • Molecular Biology 132
Replace Oscar L. Rodriguez with:
Oscar L. Rodriguez United States
Gobi Thillainadesan Canada
Changwang Deng United States
S.J.B. Cornelissen Netherlands
Qiqun Tang China
Cordula Leurs Germany
S. Hu United States
Daqian He China
Qile Hu China
Sarah Bushmeyer United States
X.‐L. Wu relative to Oscar L. Rodriguez United States Oscar L. Rodriguez's profile →
Citations per field
00.5×10×15.5×
Oscar L. Rodriguez · 1×
Citations per year

Countries citing papers authored by X.‐L. Wu

Since Specialization
Citations

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

Fields of papers citing papers by X.‐L. Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by X.‐L. Wu. 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 X.‐L. Wu. The network helps show where X.‐L. Wu may publish in the future.

Co-authors

The 25 scholars most cited alongside X.‐L. Wu, 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 X.‐L. Wu Line = papers co-authored together X.‐L. Wu links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 2013152
2 200998
3 199637
4 201332
5 202015
6 20207
7 20145
8 20203

About X.‐L. Wu

X.‐L. Wu is a scholar working on Genetics, Agronomy and Crop Science, Cancer Research, Small Animals and Molecular Biology, having authored 8 papers that have together received 349 indexed citations. Recurring topics across this work include Genetic and phenotypic traits in livestock (6 papers), Genetic Mapping and Diversity in Plants and Animals (6 papers), MicroRNA in disease regulation (1 paper), Blood groups and transfusion (1 paper), Livestock Farming and Management (1 paper), Pluripotent Stem Cells Research (1 paper), Agriculture and Biological Studies (1 paper) and Animal Behavior and Welfare Studies (1 paper). The work is most often cited by research in Cancer Research (89 citations), Genetics (163 citations), Hematology (35 citations), Plant Science (88 citations) and Molecular Biology (132 citations). X.‐L. Wu has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Ning Cai, Hui Cao, Guilherme J. M. Rosa, Daniel Gianola, Óscar González-Recio, G. de los Campos, K.A. Weigel, N. Long, Hugo Naya and Llibertat Tusell. Their work appears in journals such as Animal Genetics, Transfusion, Cell Death and Disease, Journal of Dairy Science and animal.

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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