Mingda Han

1.4k citations
42 papers · 1.2k · h-index 22

Impact in

Papers in

Mingda Han

39 papers receiving 1.2k citations

Peers

Mingda Han
Comparison fields: 5 of 88
  • Pediatrics, Perinatology and Child Health 110
  • Molecular Biology 529
  • Biomaterials 78
  • Biomedical Engineering 212
  • Rheumatology 61
Replace José Javier Martı́n de Llano with:
José Javier Martı́n de Llano Spain
Xuan Gao China
Toshiki Matsuoka Japan
Xiaomei Liu China
Yun Jun Liao China
Nicolò Salvarani Italy
Rita A. Hahn United States
Tobias Tertel Germany
Seong‐Jun Choi South Korea
Steve Oh Singapore
Mingda Han relative to José Javier Martı́n de Llano Spain José Javier Martı́n de Llano's profile →
Citations per field
00.5×2×4×5.2×
José Javier Martı́n de Llano · 1×
Citations per year

Countries citing papers authored by Mingda Han

Since Specialization
Citations

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

Fields of papers citing papers by Mingda Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010101
2 199882
3 202282
4 200576
5 202161
6 201151
7 202347
8 200946
9 200142
10 202239
11 202135
12 200634
13 202334
14 200233
15 200332
16 201431
17 202531
18 200829
19 200827
20 200524

About Mingda Han

Mingda Han is a scholar working on Molecular Biology, Biomedical Engineering, Biomaterials, Pediatrics, Perinatology and Child Health and Rheumatology, having authored 42 papers that have together received 1.2k indexed citations. Recurring topics across this work include Congenital heart defects research (13 papers), Nanoplatforms for cancer theranostics (13 papers), Nanoparticle-Based Drug Delivery (4 papers), Folate and B Vitamins Research (3 papers), Prenatal Substance Exposure Effects (3 papers), Immunotherapy and Immune Responses (3 papers), Muscle Physiology and Disorders (3 papers) and RNA modifications and cancer (2 papers). The work is most often cited by research in Pediatrics, Perinatology and Child Health (110 citations), Molecular Biology (529 citations), Biomaterials (78 citations), Biomedical Engineering (212 citations) and Rheumatology (61 citations). Mingda Han has collaborated with scholars based in United States, China and Norway. Frequent co-authors include Kérsti K. Linask, Fei Yan, Yangyang Du, Zhan Shi, Shouhua Feng, Kunxia Cao, Yue Song, Dong Hong Cai, Philip R. Brauer and Shujun Liu. Their work appears in journals such as Developmental Dynamics, Chemical Engineering Journal, American Journal of Obstetrics and Gynecology, Advanced Materials and Journal of Materials Research and Technology.

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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