Jaap G. Neels

5.1k citations
44 papers · 3.7k indexed · 2 hit papers · h-index 24

Jaap G. Neels

42 papers receiving 3.6k citations

Hit Papers

Ablation of CD11c-Positive Cells Normalizes Insulin Sensi...6742007202620132019250500750

Peers

Jaap G. Neels
Comparison fields: 5 of 106
  • Physiology 1.3k
  • Epidemiology 1.7k
  • Immunology 1.0k
  • Hematology 392
  • Endocrine and Autonomic Systems 192
Replace Reid Huber with:
Reid Huber United States
Sarah Slaymaker United States
Fahumiya Samad United States
David S. Milstone United States
Jan A. Ehses Switzerland
Joachim Fruebis United States
Prabhakara R. Nagareddy United States
Bruno Derudas France
Jeffrey L. Barnes United States
Bhama Ramkhelawon United States
Jaap G. Neels relative to Reid Huber United States Reid Huber's profile →
Citations per field
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Reid Huber · 1×
Citations per year

Countries citing papers authored by Jaap G. Neels

Since Specialization
Citations

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

Fields of papers citing papers by Jaap G. Neels

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jaap G. Neels. 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 Jaap G. Neels. The network helps show where Jaap G. Neels may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202314
2 202327
3 202373
4 20216
5 20167
6 201619
7 201323
8 201286
9 201071
10
Ablation of CD11c-Positive Cells Normalizes Insulin Sensitivity in Obese Insulin Resistant Animalsbreakdown →
2008674
11 200830
12 2007417
13
A Subpopulation of Macrophages Infiltrates Hypertrophic Adipose Tissue and Is Activated by Free Fatty Acids via Toll-like Receptors 2 and 4 and JNK-dependent Pathwaysbreakdown →
2007815
14 2007101
15 200624
16 2004168
17 200022
18 1999170
19 1999132
20 199631

About Jaap G. Neels

Jaap G. Neels is a scholar working on Rehabilitation, Hematology and Immunology, having authored 44 papers that have together received 3.7k indexed citations. Recurring topics across this work include Adipokines, Inflammation, and Metabolic Diseases (15 papers), Adipose Tissue and Metabolism (14 papers), Blood Coagulation and Thrombosis Mechanisms (9 papers), Immune Cell Function and Interaction (8 papers), Protease and Inhibitor Mechanisms (8 papers), Exercise and Physiological Responses (6 papers), Peroxisome Proliferator-Activated Receptors (6 papers) and Coagulation, Bradykinin, Polyphosphates, and Angioedema (4 papers). The work is most often cited by research in Physiology (1.3k citations), Epidemiology (1.7k citations) and Immunology (1.0k citations). Jaap G. Neels has collaborated with scholars based in France, United States and Netherlands. Frequent co-authors include Jerrold M. Olefsky, Pingping Li, David Patsouris, Justin Chapman, David J. Loskutoff, Matthew Nguyen, Svetlana Favelyukis, Christopher K. Glass, Ru Liu‐Bryan and Donna Reichart. Their work appears in journals such as Journal of Biological Chemistry, Nature Medicine and Physiological Reviews.

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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