Bin Nan

860 citations
21 papers · 633 · h-index 11

Impact in

Papers in

Bin Nan

21 papers receiving 617 citations

Peers

Bin Nan
Comparison fields: 5 of 85
  • Reproductive Medicine 115
  • Statistics and Probability 93
  • Endocrinology, Diabetes and Metabolism 175
  • Cancer Research 95
  • Pathology and Forensic Medicine 77
Replace Paulus A.H. van Noord with:
Paulus A.H. van Noord Netherlands
Shigehiro Soh Japan
Susan B. Brown United States
Neil M. Schultz United States
Milena Braga‐Basaria United States
Eric A. W. Slob United Kingdom
J. Blom Netherlands
Marit Holmqvist Sweden
Peggy Wan United States
P Stattin Sweden
Bin Nan relative to Paulus A.H. van Noord Netherlands Paulus A.H. van Noord's profile →
Citations per field
00.5×3.7×
Paulus A.H. van Noord · 1×
Citations per year

Countries citing papers authored by Bin Nan

Since Specialization
Citations

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

Fields of papers citing papers by Bin Nan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007203
2 200683
3 200778
4 200655
5 201554
6 200928
7 201426
8 201623
9 200719
10 200815
11 201312
12 20117
13 20086
14 20225
15 20135
16 20135
17 20184
18 20132
19 20111
20 20131

About Bin Nan

Bin Nan is a scholar working on Endocrinology, Diabetes and Metabolism, Statistics and Probability, Pathology and Forensic Medicine, Genetics and Epidemiology, having authored 21 papers that have together received 633 indexed citations. Recurring topics across this work include Statistical Methods and Inference (8 papers), Menopause: Health Impacts and Treatments (6 papers), Phytoestrogen effects and research (5 papers), Statistical Methods and Bayesian Inference (4 papers), Hormonal and reproductive studies (3 papers), Advanced Causal Inference Techniques (3 papers), Ovarian function and disorders (3 papers) and Genetic and phenotypic traits in livestock (2 papers). The work is most often cited by research in Reproductive Medicine (115 citations), Statistics and Probability (93 citations), Endocrinology, Diabetes and Metabolism (175 citations), Cancer Research (95 citations) and Pathology and Forensic Medicine (77 citations). Bin Nan has collaborated with scholars based in United States, Australia and Canada. Frequent co-authors include Roderick J. A. Little, Sioḃán D. Harlow, Sybil L. Crawford, Ellen Sullivan Mitchell, John Taffe, Cornelia L. Trimble, Ichiro Ota, Stephen J. Weiss, Eric R. Fearon and Rork Kuick. Their work appears in journals such as Obesity, The Journal of Clinical Endocrinology & Metabolism, Lifetime Data Analysis, Biometrics and Annals of the Rheumatic Diseases.

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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