Cody Ashby
Impact in
- Hematology top 5%
- Multiple Myeloma Research and Treatments
-
- Genomics and Phylogenetic Studies
- Protein Degradation and Inhibitors
- Ubiquitin and proteasome pathways
- RNA modifications and cancer
- RNA and protein synthesis mechanisms
- RNA Research and Splicing
Papers in
- Hematology 34
- Multiple Myeloma Research and Treatments 33
-
- Protein Degradation and Inhibitors 10
- Ubiquitin and proteasome pathways 5
- Glycosylation and Glycoproteins Research 4
- Molecular Biology Techniques and Applications 3
- Co-authors
- Xiuzhen Huang (5 shared papers)Carole L. Cramer (2 shared papers)Guojun Li (2 shared papers)Zheng Chang (2 shared papers)Yu Zhang (1 shared paper)Deli Liu (1 shared paper)Juntao Liu (1 shared paper)Gareth J. Morgan (26 shared papers)
- Journals
- Blood (18 papers)Haematologica (4 papers)BMC Bioinformatics (3 papers)Blood Cancer Journal (2 papers)Leukemia (2 papers)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Cody Ashby
42 papers receiving 532 citations
Peers
Comparison fields: 5 of 80
- Hematology 155
- Molecular Biology 314
- Cancer Research 60
- Oncology 75
- Genetics 70
Countries citing papers authored by Cody Ashby
This map shows the geographic impact of Cody Ashby'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 Cody Ashby with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cody Ashby more than expected).
Fields of papers citing papers by Cody Ashby
This network shows the impact of papers produced by Cody Ashby. 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 Cody Ashby. The network helps show where Cody Ashby may publish in the future.
Co-authors
The 25 scholars most cited alongside Cody Ashby, 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 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 204 | |
| 2 | 2018 | 36 | |
| 3 | 2022 | 30 | |
| 4 | 2021 | 28 | |
| 5 | 2020 | 24 | |
| 6 | 2020 | 23 | |
| 7 | 2020 | 22 | |
| 8 | 2024 | 16 | |
| 9 | 2022 | 13 | |
| 10 | 2019 | 13 | |
| 11 | 2022 | 12 | |
| 12 | 2021 | 12 | |
| 13 | 2023 | 11 | |
| 14 | 2018 | 11 | |
| 15 | 2013 | 9 | |
| 16 | 2015 | 8 | |
| 17 | 2021 | 6 | |
| 18 | 2015 | 6 | |
| 19 | 2024 | 6 | |
| 20 | 2019 | 4 |
About Cody Ashby
Cody Ashby is a scholar working on Hematology, Molecular Biology, Cancer Research, Oncology and Pathology and Forensic Medicine, having authored 46 papers that have together received 538 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (33 papers), Protein Degradation and Inhibitors (10 papers), Cancer Genomics and Diagnostics (9 papers), Ubiquitin and proteasome pathways (5 papers), Glycosylation and Glycoproteins Research (4 papers), Peptidase Inhibition and Analysis (4 papers), Molecular Biology Techniques and Applications (3 papers) and Cancer Mechanisms and Therapy (3 papers). The work is most often cited by research in Hematology (155 citations), Molecular Biology (314 citations), Cancer Research (60 citations), Oncology (75 citations) and Genetics (70 citations). Cody Ashby has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Xiuzhen Huang, Carole L. Cramer, Guojun Li, Zheng Chang, Yu Zhang, Deli Liu, Juntao Liu, Gareth J. Morgan, Brian A. Walker and Michael Bauer. Their work appears in journals such as Blood, Haematologica, BMC Bioinformatics, Blood Cancer Journal and Leukemia.
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.