Wayne R. Danter

489 citations
15 papers · 347 · h-index 8

Impact in

Papers in

    • CRISPR and Genetic Engineering 4
    • Single-cell and spatial transcriptomics 3
    • Pluripotent Stem Cells Research 3
    • Cancer therapeutics and mechanisms 2
    • SARS-CoV-2 and COVID-19 Research 3

Wayne R. Danter

13 papers receiving 326 citations

Peers

Wayne R. Danter
Comparison fields: 5 of 71
  • Endocrine and Autonomic Systems 41
  • Oncology 153
  • Biotechnology 31
  • Physiology 76
  • Cancer Research 40
Replace Takuya Kawata with:
Takuya Kawata Japan
Thomas Jackson United Kingdom
Wenshan Zhao China
Ilaria Cerbara Italy
Jiayi Wu China
Teneille Walker United States
Alberto Contreras‐Sanz Canada
Lola E. Navas Spain
E. M. Link United Kingdom
Gunjan Gakhar United States
Wayne R. Danter relative to Takuya Kawata Japan Takuya Kawata's profile →
Citations per field
00.5×3.7×
Takuya Kawata · 1×
Citations per year

Countries citing papers authored by Wayne R. Danter

Since Specialization
Citations

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

Fields of papers citing papers by Wayne R. Danter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wayne R. Danter. 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 Wayne R. Danter. The network helps show where Wayne R. Danter may publish in the future.

Co-authors

The 9 scholars most cited alongside Wayne R. Danter, 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 Wayne R. Danter Line = papers co-authored together Wayne R. Danter links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 2016130
2 199976
3 201839
4 201922
5 201621
6 202020
7 201913
8 202110
9 20216
10 20213
11 20202
12 20212
13
Molecular data mining tool: advances in HIV research
20001
14 20171
15 20001

About Wayne R. Danter

Wayne R. Danter is a scholar working on Molecular Biology, Infectious Diseases, Pulmonary and Respiratory Medicine, Oncology and Physiology, having authored 15 papers that have together received 347 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (4 papers), Single-cell and spatial transcriptomics (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Pluripotent Stem Cells Research (3 papers), Cancer therapeutics and mechanisms (2 papers), Pancreatic function and diabetes (1 paper), Neuroscience of respiration and sleep (1 paper) and Cell Image Analysis Techniques (1 paper). The work is most often cited by research in Endocrine and Autonomic Systems (41 citations), Oncology (153 citations), Biotechnology (31 citations), Physiology (76 citations) and Cancer Research (40 citations). Wayne R. Danter has collaborated with scholars based in Canada, United States and Spain. Frequent co-authors include Saman Maleki Vareki, James Koropatnick, Sally Esmail, Serban San‐Marina, R. R. F. Ruby, Peter Eng, Charles F. George, Neville Suskin and Gerald Wisenberg. Their work appears in journals such as Clinical Cancer Research, Frontiers in Aging Neuroscience, Orphanet Journal of Rare Diseases, Frontiers in Cell and Developmental Biology and Computational and Structural Biotechnology Journal.

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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