Xingbin Wang

1.5k citations
32 papers · 657 · h-index 18

Impact in

Papers in

    • Genetic Associations and Epidemiology 8
    • Diabetes and associated disorders 3
    • Bioinformatics and Genomic Networks 4

Xingbin Wang

32 papers receiving 645 citations

Peers

Xingbin Wang
Comparison fields: 5 of 84
  • Biological Psychiatry 28
  • Neurology 64
  • Genetics 184
  • Physiology 150
  • Behavioral Neuroscience 20
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Rita Cittadella Italy
Stacey Melquist United States
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Andrea Saul Costa Italy
Ekaterina Zakharova Russia
Roger Willian de Lábio Brazil
Brandon C. Sos United States
Krystyna Mitosek‐Szewczyk Poland
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Citations per field
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Citations per year

Countries citing papers authored by Xingbin Wang

Since Specialization
Citations

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

Fields of papers citing papers by Xingbin Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201252
2 201547
3 201446
4 201544
5 201841
6 201437
7 201531
8 201928
9 201428
10 201528
11
Beta-amyloid toxicity modifier genes and the risk of Alzheimer's disease.
201227
12 201424
13 201323
14 201521
15 201520
16 201419
17 201917
18 201517
19 201315
20 201515

About Xingbin Wang

Xingbin Wang is a scholar working on Genetics, Molecular Biology, Surgery, Cardiology and Cardiovascular Medicine and Endocrinology, Diabetes and Metabolism, having authored 32 papers that have together received 657 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (8 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers), Lipoproteins and Cardiovascular Health (5 papers), Alzheimer's disease research and treatments (4 papers), Bioinformatics and Genomic Networks (4 papers), Lipid metabolism and disorders (4 papers), Diabetes and associated disorders (3 papers) and Cancer, Lipids, and Metabolism (3 papers). The work is most often cited by research in Biological Psychiatry (28 citations), Neurology (64 citations), Genetics (184 citations), Physiology (150 citations) and Behavioral Neuroscience (20 citations). Xingbin Wang has collaborated with scholars based in United States, Pakistan and Canada. Frequent co-authors include M. Ilyas Kamboh, F. Yesim Demirci, M. Michael Barmada, Oscar L. López, Samantha L. Rosenthal, Etienne Sibille, George C. Tseng, Mikhil Bamne, Beth E. Snitz and Eleanor Feingold. Their work appears in journals such as PLoS ONE, Neurobiology of Aging, Journal of Alzheimer s Disease, Journal of Lipid Research and Metabolism.

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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