DA Williams

1.8k citations
37 papers · 1.5k indexed · h-index 16
  • Hematology top 2%
    • Hematopoietic Stem Cell Transplantation 18
  • Immunology top 5%
    • Immune Cell Function and Interaction 6
    • Immune Response and Inflammation 5
  • Oncology top 10%
    • Cancer Cells and Metastasis 5
    • Neutropenia and Cancer Infections 4
  • Genetics top 10%
    • Virus-based gene therapy research 13
  • Genetics top 5%
    • Virus-based gene therapy research 13
    • 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 81
  • Hematology 460
  • Immunology 599
  • Oncology 444
  • Genetics 140
  • Genetics 366
Replace Yuji Kashiwakura with:
Yuji Kashiwakura Japan
Farshid N. Rouhani United States
S Neben United States
D Grail Australia
S Suematsu Japan
Hilary J. McKenna Canada
F W Ruscetti United States
Masatsugu Ohta Japan
JR Keller United States
Anand S. Lagoo United States
DA Williams relative to Yuji Kashiwakura Japan Yuji Kashiwakura's profile →
Citations per field
00.5×1.7×
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-authorship network

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
#Work
1 200014
2 20007
3 1996158
4 19968
5 1995212
6 1994153
7 199417
8 1994128
9 199466
10 1994161
11 199339
12 19934
13 19937
14 19931
15 19926
16 19917
17 199167
18
In search of the self-renewing hematopoietic stem cell.
19914
19
Embryonic stem cells as targets for gene transfer: a new approach to molecular manipulation of the murine hematopoietic system.
19902
20 198824

About DA Williams

DA Williams is a scholar working on Hematology, Genetics and Immunology, 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 Neutropenia and Cancer Infections (4 papers). The work is most often cited by research in Hematology (460 citations), Immunology (599 citations) and Oncology (444 citations). DA Williams has collaborated with scholars based in United States. Frequent co-authors include XX Du, Attilio Orazi, C. M. Doerschuk, Akihiko Gotoh, J Nishimaki, Keisuke Toyama, Keisuke Miyazawa, HE Broxmeyer, Samuel Goldman and MC Yoder. 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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