David A. Williams

31.8k citations
338 papers · 21.2k indexed · 5 hit papers · h-index 74
Topics
Virus-based gene therapy research (74 papers)CRISPR and Genetic Engineering (53 papers)RNA Interference and Gene Delivery (48 papers)

In The Last Decade

David A. Williams

327 papers receiving 20.7k citations

Hit Papers

Haematopoietic stem cells do not transdifferentiate i...19902026200220142004199019951996201450010001.5k

Peers

David A. Williams
Comparison fields: 5 of 170
  • Molecular Biology 11.0k
  • Immunology 5.5k
  • Genetics 4.7k
  • Hematology 3.6k
  • Oncology 3.6k
Replace Tatsutoshi Nakahata with:
Tatsutoshi Nakahata Japan
Leonard D. Shultz United States
R. Keith Humphries Canada
Hiromitsu Nakauchi Japan
Olivier Hermine France
Malcolm A.S. Moore United States
Frédéric J. de Sauvage United States
Ramesh A. Shivdasani United States
Françoise Le Deist France
Smith Rjh Sweden
David A. Williams relative to Tatsutoshi Nakahata Japan Tatsutoshi Nakahata's profile →
Citations per field
00.5×1.5×2.2×
Tatsutoshi Nakahata · 1×
Citations per year

Countries citing papers authored by David A. Williams

Since Specialization
Citations

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

Fields of papers citing papers by David A. Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David A. Williams

This figure shows the co-authorship network connecting the top 25 collaborators of David A. Williams. A scholar is included among the top collaborators of David A. Williams based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David A. Williams. David A. Williams is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 3
4 1
5 15
6 2
7 59
8 24
9
Constitutional traditions in Maori interactions with the crown
0
10 126
11 48
12 71
13 17
14 49
15 104
16 4
17 0
18 57
19
Analysis of steel factor (stem cell factor) isoforms in the hematopoietic microenvironment.
7
20 6

About David A. Williams

David A. Williams is a scholar working on Hematology, Genetics and Immunology, having authored 338 papers that have together received 21.2k indexed citations. Recurring topics across this work include Virus-based gene therapy research (74 papers), CRISPR and Genetic Engineering (53 papers) and RNA Interference and Gene Delivery (48 papers). The work is most often cited by research in Hematology (3.6k citations), Genetics (3.0k citations) and Immunology (5.5k citations). David A. Williams has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include José A. Cancelas, Xunxiang Du, Yi Zheng, Helmut Hanenberg, Steven Lane, Tassilo Moritz, Ikunoshin Kato, Xiang Xiao, Fiona M. Watt and Mary C. Dinauer. Their work appears in journals such as Nature, Science and New England Journal of Medicine.

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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