DA Williams

879 citations
15 papers · 743 indexed · h-index 7

Impact in

  • Hematology top 5%
    • Hematopoietic Stem Cell Transplantation
  • Genetics top 5%
    • Virus-based gene therapy research
    • Mesenchymal stem cell research

Papers in

    • Virus-based gene therapy research 5
    • CAR-T cell therapy research 3

DA Williams

14 papers receiving 722 citations

Peers

DA Williams
Comparison fields: 5 of 59
  • Hematology 190
  • Genetics 407
  • Genetics 92
  • Oncology 203
  • Molecular Biology 425
Replace Laura M. Tuschong with:
Laura M. Tuschong United States
Z. Zu United States
Narda Whiting‐Theobald United States
Jiahua Qian United States
Maureen Ward United States
HP Kiem United States
M.K. Brenner United States
CL Reading United States
Irina Kondratenko Russia
Sergio Vai Italy
DA Williams relative to Laura M. Tuschong United States Laura M. Tuschong's profile →
Citations per field
00.5×1.6×
Laura M. Tuschong · 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

15 of 15 papers shown
#Work
1 20166
2 20133
3
The Characteristics of International Joint Ventures in Thailand
20100
4 20091
5
Sindrome da malassorbimento in un gatto con Leishmaniosi.
20053
6 200370
7
Release of mitochondrial Ca2 via the permeability transition activates endoplasmic reticulum Ca2 uptake
20011
8 19945
9 1993141
10 1993160
11 1993107
12 1992118
13 1990116
14 19905
15 19857

About DA Williams

DA Williams is a scholar working on Genetics, Oncology, Hematology, Complementary and alternative medicine and General Economics, Econometrics and Finance, having authored 15 papers that have together received 743 indexed citations. Recurring topics across this work include Virus-based gene therapy research (5 papers), CAR-T cell therapy research (3 papers), RNA Interference and Gene Delivery (3 papers), CRISPR and Genetic Engineering (3 papers), Hematopoietic Stem Cell Transplantation (2 papers), Advanced Breast Cancer Therapies (1 paper), Mitochondrial Function and Pathology (1 paper) and Nail Diseases and Treatments (1 paper). The work is most often cited by research in Hematology (190 citations), Genetics (407 citations), Genetics (92 citations), Oncology (203 citations) and Molecular Biology (425 citations). DA Williams has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Di Martin, T Moritz, DM Bodine, AW Nienhuis, SH Orkin, RE Donahue, Margery Rosenblatt, K M Zsebo, Lisa K. Jacobs and Davina Porock. Their work appears in journals such as Blood, Value in Health, Biophysical Journal, Cancer Research and Experimental Physiology.

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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