Jack Heath

1.5k citations
20 papers · 1.2k indexed · h-index 14

Impact in

  • Nephrology top 2%
    • Parathyroid Disorders and Treatments
    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research

Papers in

    • Neutrophil, Myeloperoxidase and Oxidative Mechanisms 2
    • RNA Interference and Gene Delivery 3
    • Glycosylation and Glycoproteins Research 2
    • TGF-β signaling in diseases 2

Jack Heath

18 papers receiving 1.2k citations

Peers

Jack Heath
Comparison fields: 5 of 92
  • Nephrology 239
  • Cancer Research 167
  • Immunology 197
  • Molecular Biology 614
  • Cell Biology 136
Replace Kaiyu Yuan with:
Kaiyu Yuan United States
Serge Lemay Canada
Martina Leopizzi Italy
Fenghua Zeng United States
Chunping Yu China
Jiayi Yao China
Nerea Méndez‐Barbero Spain
Karl X. Knaup Germany
George T. Tkalcevic United States
Jack Heath relative to Kaiyu Yuan United States Kaiyu Yuan's profile →
Citations per field
00.5×1.5×2.3×
Kaiyu Yuan · 1×
Citations per year

Countries citing papers authored by Jack Heath

Since Specialization
Citations

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

Fields of papers citing papers by Jack Heath

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20241
4 20238
5 20201
6 201923
7 20171
8 201737
9 201765
10 2016132
11 201643
12 201543
13 2014103
14 2014130
15 2012270
16 2011146
17 200913
18 200932
19 200924
20 2008129

About Jack Heath

Jack Heath is a scholar working on Immunology, Molecular Biology, Genetics, Urology and Rehabilitation, having authored 20 papers that have together received 1.2k indexed citations. Recurring topics across this work include Virus-based gene therapy research (3 papers), Cardiac Valve Diseases and Treatments (3 papers), RNA Interference and Gene Delivery (3 papers), Glycosylation and Glycoproteins Research (2 papers), Viral gastroenteritis research and epidemiology (2 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (2 papers), Prenatal Screening and Diagnostics (2 papers) and TGF-β signaling in diseases (2 papers). The work is most often cited by research in Nephrology (239 citations), Cancer Research (167 citations), Immunology (197 citations), Molecular Biology (614 citations) and Cell Biology (136 citations). Jack Heath has collaborated with scholars based in United States, Netherlands and Australia. Frequent co-authors include Yabing Chen, Chang Hyun Byon, Yong Sun, Kaiyu Yuan, Xia Mao, Peter G. Anderson, Hui Wu, Hanjoong Jo, Jianfeng Chen and Kui Zhang. Their work appears in journals such as Blood, Molecular Therapy, Arteriosclerosis Thrombosis and Vascular Biology, Circulation Research and Scientific Reports.

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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