Darrell Nix
Impact in
- Hematology top 2%
- Multiple Myeloma Research and Treatments
- Oncology top 10%
- Peptidase Inhibition and Analysis
Papers in
-
- Protein Degradation and Inhibitors 4
- Histone Deacetylase Inhibitors Research 3
- Ubiquitin and proteasome pathways 2
- Fibroblast Growth Factor Research 2
- Oncology 5
- Peptidase Inhibition and Analysis 4
- Co-authors
- Dixie Esseltine (2 shared papers)J J Schentag (2 shared papers)Timothy Madden (1 shared paper)Randall E. Millikan (1 shared paper)Shi‐Ming Tu (1 shared paper)Hong Yang (1 shared paper)Lance C. Pagliaro (1 shared paper)Danai Daliani (1 shared paper)
- Journals
- Journal of Clinical Oncology (3 papers)Drug Metabolism and Disposition (2 papers)Blood (2 papers)Xenobiotica (2 papers)Antimicrobial Agents and Chemotherapy (2 papers)
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
Darrell Nix
20 papers receiving 874 citations
Peers
Comparison fields: 5 of 81
- Hematology 338
- Oncology 263
- Molecular Biology 521
- Pharmacology 76
- Cancer Research 65
Countries citing papers authored by Darrell Nix
This map shows the geographic impact of Darrell Nix'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 Darrell Nix with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Darrell Nix more than expected).
Fields of papers citing papers by Darrell Nix
This network shows the impact of papers produced by Darrell Nix. 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 Darrell Nix. The network helps show where Darrell Nix may publish in the future.
Co-authors
The 25 scholars most cited alongside Darrell Nix, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 385 | |
| 2 | 2005 | 181 | |
| 3 | 2005 | 117 | |
| 4 | 1985 | 70 | |
| 5 | 2017 | 36 | |
| 6 | 2006 | 29 | |
| 7 | 2009 | 16 | |
| 8 | 2024 | 16 | |
| 9 | 1991 | 14 | |
| 10 | 2009 | 7 | |
| 11 | 1997 | 7 | |
| 12 | 2020 | 7 | |
| 13 | 1990 | 7 | |
| 14 | 2020 | 6 | |
| 15 | 2016 | 4 | |
| 16 | 2009 | 3 | |
| 17 | 2018 | 3 | |
| 18 | 2020 | 3 | |
| 19 | 2020 | 2 | |
| 20 | 2024 | 1 |
About Darrell Nix
Darrell Nix is a scholar working on Molecular Biology, Oncology, Hematology, Infectious Diseases and Pharmacology, having authored 21 papers that have together received 914 indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (4 papers), Multiple Myeloma Research and Treatments (4 papers), Peptidase Inhibition and Analysis (4 papers), Histone Deacetylase Inhibitors Research (3 papers), Ubiquitin and proteasome pathways (2 papers), Antibiotics Pharmacokinetics and Efficacy (2 papers), HIV/AIDS drug development and treatment (2 papers) and Fibroblast Growth Factor Research (2 papers). The work is most often cited by research in Hematology (338 citations), Oncology (263 citations), Molecular Biology (521 citations), Pharmacology (76 citations) and Cancer Research (65 citations). Darrell Nix has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Dixie Esseltine, J J Schentag, Timothy Madden, Randall E. Millikan, Shi‐Ming Tu, Hong Yang, Lance C. Pagliaro, Danai Daliani, Cherie Perez and Christos N. Papandreou. Their work appears in journals such as Journal of Clinical Oncology, Drug Metabolism and Disposition, Blood, Xenobiotica and Antimicrobial Agents and Chemotherapy.
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.