Daniel J. Pearce

4.7k citations
91 papers · 3.2k · h-index 30

Impact in

  • Hematology top 2%
    • Acute Myeloid Leukemia Research
    • Hematopoietic Stem Cell Transplantation
  • Immunology top 5%
    • Psoriasis: Treatment and Pathogenesis

Papers in

Daniel J. Pearce

91 papers receiving 3.2k citations

Peers

Daniel J. Pearce
Comparison fields: 5 of 154
  • Hematology 537
  • Immunology 801
  • Dermatology 279
  • Condensed Matter Physics 287
  • Oncology 516
Replace Tim Lämmermann with:
Tim Lämmermann Germany
Eva‐B. Bröcker Germany
Heather E. Fleming United States
Ming‐Jer Tang Taiwan
Irina B. Mazo United States
Minoru Tanaka Japan
Ying Tang China
Weiqun Peng United States
Lisa Cameron United States
Yoshihiro Asano Japan
Daniel J. Pearce relative to Tim Lämmermann Germany Tim Lämmermann's profile →
Citations per field
00.5×3.3×
Tim Lämmermann · 1×
Citations per year

Countries citing papers authored by Daniel J. Pearce

Since Specialization
Citations

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

Fields of papers citing papers by Daniel J. Pearce

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel J. Pearce. 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 Daniel J. Pearce. The network helps show where Daniel J. Pearce may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008280
2 2001278
3 2005236
4 2012225
5 2005178
6 2014137
7 2005100
8 201796
9 200491
10 201090
11 200681
12 200368
13 200763
14 200962
15 200762
16 200659
17 201253
18 200351
19 201743
20 201143

About Daniel J. Pearce

Daniel J. Pearce is a scholar working on Immunology, Molecular Biology, Hematology, Condensed Matter Physics and Dermatology, having authored 91 papers that have together received 3.2k indexed citations. Recurring topics across this work include Psoriasis: Treatment and Pathogenesis (26 papers), Micro and Nano Robotics (12 papers), Hematopoietic Stem Cell Transplantation (9 papers), Dermatology and Skin Diseases (5 papers), Immune Cell Function and Interaction (5 papers), Nonmelanoma Skin Cancer Studies (5 papers), Acute Myeloid Leukemia Research (4 papers) and Nonlinear Dynamics and Pattern Formation (4 papers). The work is most often cited by research in Hematology (537 citations), Immunology (801 citations), Dermatology (279 citations), Condensed Matter Physics (287 citations) and Oncology (516 citations). Daniel J. Pearce has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Steven R. Feldman, Dominique Bonnet, T. Andrew Lister, David Taussig, Rajesh Balkrishnan, Louis C. Argenta, Michael J. Morykwas, Byron J. Faler, Christopher M. Ridler and Alan B. Fleischer. Their work appears in journals such as Journal of Dermatological Treatment, Physical Review Letters, Dermatologic Surgery, Experimental Hematology and Blood.

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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