DA Williams

1.8k citations
37 papers · 1.5k · h-index 16

Impact in

  • Hematology top 2%
    • Hematopoietic Stem Cell Transplantation
    • Platelet Disorders and Treatments
  • Immunology top 5%
    • Immune Cell Function and Interaction
    • Toxin Mechanisms and Immunotoxins

Papers in

    • Hematopoietic Stem Cell Transplantation 18
    • RNA Interference and Gene Delivery 10
    • CRISPR and Genetic Engineering 8

DA Williams

37 papers receiving 1.5k citations

Peers

DA Williams
Comparison fields: 5 of 78
  • Hematology 449
  • Immunology 571
  • Oncology 411
  • Genetics 134
  • Genetics 353
Replace Yuji Kashiwakura with:
Yuji Kashiwakura Japan
D Grail Australia
S Suematsu Japan
Masatsugu Ohta Japan
Lucia Dora Notarangelo Italy
Anand S. Lagoo United States
J R Keller United States
Manjiri Sathe United States
Philippe Guardiola France
Manabu Musashi Japan
DA Williams relative to Yuji Kashiwakura Japan Yuji Kashiwakura's profile →
Citations per field
00.5×1.5×1.9×
Yuji Kashiwakura · 1×
Citations per year

Countries citing papers authored by DA Williams

Since Specialization
Citations

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

Fields of papers citing papers by DA Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1995213
2 1994161
3 1996158
4 1994153
5 1994128
6 1993112
7 199384
8 199172
9 199167
10 199466
11 199339
12 199536
13 199627
14 198824
15 199521
16 199417
17 200014
18 199610
19 199310
20 199110

About DA Williams

DA Williams is a scholar working on Hematology, Molecular Biology, Genetics, Immunology and Oncology, having authored 37 papers that have together received 1.5k indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (18 papers), Virus-based gene therapy research (13 papers), RNA Interference and Gene Delivery (10 papers), CRISPR and Genetic Engineering (8 papers), Immune Cell Function and Interaction (6 papers), Cancer Cells and Metastasis (5 papers), Immune Response and Inflammation (5 papers) and Immunotherapy and Immune Responses (4 papers). The work is most often cited by research in Hematology (449 citations), Immunology (571 citations), Oncology (411 citations), Genetics (134 citations) and Genetics (353 citations). DA Williams has collaborated with scholars based in United States and Japan. Frequent co-authors include XX Du, Attilio Orazi, HE Broxmeyer, Keisuke Miyazawa, Keisuke Toyama, Akihiko Gotoh, C. M. Doerschuk, J Nishimaki, Samuel Goldman and Tassilo Moritz. Their work appears in journals such as Blood, Bone Marrow Transplantation, Seminars in Hematology and PubMed.

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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