Ning-Yuan Chen

842 citations
11 papers · 596 · h-index 11

Impact in

Papers in

Ning-Yuan Chen

11 papers receiving 582 citations

Peers

Ning-Yuan Chen
Comparison fields: 5 of 57
  • Physiology 74
  • Pulmonary and Respiratory Medicine 192
  • Immunology 115
  • Genetics 123
  • Cancer Research 55
Replace Marcello Baroni with:
Marcello Baroni Italy
AM Randi United Kingdom
Yichun Yang China
Ren An China
Benjamin L. Green United States
Sili Zou China
Joeffrey Chahine United States
Simon C. Rowan Ireland
Stephen G. Romansky United States
Emiko Maeda Japan
Ning-Yuan Chen relative to Marcello Baroni Italy Marcello Baroni's profile →
Citations per field
00.5×6.2×
Marcello Baroni · 1×
Citations per year

Countries citing papers authored by Ning-Yuan Chen

Since Specialization
Citations

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

Fields of papers citing papers by Ning-Yuan Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ning-Yuan Chen. 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 Ning-Yuan Chen. The network helps show where Ning-Yuan Chen may publish in the future.

Co-authors

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

All Works

11 of 11 papers shown
#Work
1 2017124
2 200089
3 201669
4 200164
5 201657
6 201351
7 201446
8 201537
9 201928
10 201820
11 201711

About Ning-Yuan Chen

Ning-Yuan Chen is a scholar working on Pulmonary and Respiratory Medicine, Surgery, Molecular Biology, Cardiology and Cardiovascular Medicine and Genetics, having authored 11 papers that have together received 596 indexed citations. Recurring topics across this work include Pulmonary Hypertension Research and Treatments (4 papers), Diabetes and associated disorders (2 papers), T-cell and B-cell Immunology (2 papers), Cardiovascular Function and Risk Factors (2 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (2 papers), Immune Cell Function and Interaction (2 papers), Ubiquitin and proteasome pathways (1 paper) and Adenosine and Purinergic Signaling (1 paper). The work is most often cited by research in Physiology (74 citations), Pulmonary and Respiratory Medicine (192 citations), Immunology (115 citations), Genetics (123 citations) and Cancer Research (55 citations). Ning-Yuan Chen has collaborated with scholars based in United States, Germany and China. Frequent co-authors include Jie Tang, F. Susan Wong, Harry Karmouty‐Quintana, Wen Li, Michael R. Blackburn, Tingting Weng, Brian A. Bruckner, Robert Sherwin, Luis J. Garcia‐Morales and R.R. Bunge. Their work appears in journals such as The Journal of Experimental Medicine, American Journal of Respiratory Cell and Molecular Biology, Pediatric Research, Journal of Clinical Investigation and American Journal of Respiratory and Critical Care Medicine.

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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