Jacklyn Whitehead

770 citations
10 papers · 623 · h-index 10

Impact in

  • Genetics top 5%
    • Mesenchymal stem cell research
  • Biomaterials top 10%
    • Electrospun Nanofibers in Biomedical Applications

Papers in

Jacklyn Whitehead

10 papers receiving 618 citations

Peers

Jacklyn Whitehead
Comparison fields: 5 of 77
  • Genetics 170
  • Biomaterials 159
  • Rehabilitation 68
  • Molecular Medicine 41
  • Urology 40
Replace Dejie Zhou with:
Dejie Zhou United States
Kaitlin C. Murphy United States
Forough Azam Sayahpour Iran
Ektoras Hadjipanayi Germany
Daniel A. Young United States
Guo-Shiang Huang Taiwan
Yongjie Zhang China
Zuzana Kočí Czechia
Maximilian G. Burger Switzerland
In‐Su Park South Korea
Jacklyn Whitehead relative to Dejie Zhou United States Dejie Zhou's profile →
Citations per field
00.5×1.5×
Dejie Zhou · 1×
Citations per year

Countries citing papers authored by Jacklyn Whitehead

Since Specialization
Citations

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

Fields of papers citing papers by Jacklyn Whitehead

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Jacklyn Whitehead, 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 Jacklyn Whitehead Line = papers co-authored together Jacklyn Whitehead links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 2017154
2 2017117
3 201784
4 202073
5 201766
6 201542
7 201929
8 201829
9 201817
10 201912

About Jacklyn Whitehead

Jacklyn Whitehead is a scholar working on Genetics, Biomedical Engineering, Surgery, Molecular Biology and Rehabilitation, having authored 10 papers that have together received 623 indexed citations. Recurring topics across this work include Mesenchymal stem cell research (7 papers), 3D Printing in Biomedical Research (4 papers), Tissue Engineering and Regenerative Medicine (4 papers), Bone Tissue Engineering Materials (3 papers), Electrospun Nanofibers in Biomedical Applications (2 papers), Wound Healing and Treatments (2 papers), Neuroscience and Neural Engineering (1 paper) and Indoor Air Quality and Microbial Exposure (1 paper). The work is most often cited by research in Genetics (170 citations), Biomaterials (159 citations), Rehabilitation (68 citations), Molecular Medicine (41 citations) and Urology (40 citations). Jacklyn Whitehead has collaborated with scholars based in United States and Russia. Frequent co-authors include J. Kent Leach, Dejie Zhou, Kaitlin C. Murphy, Steve S. Ho, Charlotte E. Vorwald, Scott I. Simon, Katherine H. Griffin, Marissa Gionet‐Gonzales, Gang-yu Liu and Jiali Zhang. Their work appears in journals such as Stem Cells, Biomaterials, The Journal of Physical Chemistry B, Toxicological Sciences and Advanced Biosystems.

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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