Daniel C. McQuaid
Impact in
- Hematology top 10%
- Multiple Myeloma Research and Treatments
- Oncology top 10%
- Peptidase Inhibition and Analysis
- CAR-T cell therapy research
Papers in
-
- Multiple Myeloma Research and Treatments 1
- Acute Myeloid Leukemia Research 1
-
- Lymphoma Diagnosis and Treatment 2
- Co-authors
- Jing Wang (1 shared paper)Yimin Qian (1 shared paper)John F. Hines (1 shared paper)Saul Jaime‐Figueroa (1 shared paper)Andrew P. A. Crew (1 shared paper)Momar Toure (1 shared paper)Craig M. Crews (1 shared paper)Blake E. Smith (1 shared paper)
- Journals
- Human Pathology (1 paper)Cancer Discovery (1 paper)Cell chemical biology (1 paper)Cancer Research (1 paper)American Journal of Clinical Pathology (1 paper)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Daniel C. McQuaid
6 papers receiving 759 citations
Daniel C. McQuaid's Hit Papers
Peers
Comparison fields: 5 of 50
- Hematology 157
- Oncology 307
- Molecular Biology 670
- Cancer Research 40
- Genetics 25
Countries citing papers authored by Daniel C. McQuaid
This map shows the geographic impact of Daniel C. McQuaid'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 Daniel C. McQuaid with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel C. McQuaid more than expected).
Fields of papers citing papers by Daniel C. McQuaid
This network shows the impact of papers produced by Daniel C. McQuaid. 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 Daniel C. McQuaid. The network helps show where Daniel C. McQuaid may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel C. McQuaid, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | The Advantages of Targeted Protein Degradation Over Inhibition: An RTK Case Study Hit paper breakdown → | 2017 | 557 |
| 2 | 2017 | 156 | |
| 3 | 2018 | 59 | |
| 4 | 2022 | 7 | |
| 5 | 2022 | 5 | |
| 6 | 2025 | 2 | |
| 7 | 2026 | 0 |
About Daniel C. McQuaid
Daniel C. McQuaid is a scholar working on Hematology, Pathology and Forensic Medicine, Pulmonary and Respiratory Medicine, Molecular Biology and Cancer Research, having authored 7 papers that have together received 786 indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (3 papers), Lymphoma Diagnosis and Treatment (2 papers), Multiple Myeloma Research and Treatments (1 paper), Acute Myeloid Leukemia Research (1 paper), Protein Degradation and Inhibitors (1 paper), Immune Cell Function and Interaction (1 paper), Ferroptosis and cancer prognosis (1 paper) and RNA modifications and cancer (1 paper). The work is most often cited by research in Hematology (157 citations), Oncology (307 citations), Molecular Biology (670 citations), Cancer Research (40 citations) and Genetics (25 citations). Daniel C. McQuaid has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Jing Wang, Yimin Qian, John F. Hines, Saul Jaime‐Figueroa, Andrew P. A. Crew, Momar Toure, Craig M. Crews, Blake E. Smith, Hanqing Dong and Daniel P. Bondeson. Their work appears in journals such as Human Pathology, Cancer Discovery, Cell chemical biology, Cancer Research and American Journal of Clinical Pathology.
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.