Kim Last
Impact in
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- Lymphoma Diagnosis and Treatment
- Genetics top 5%
- Chronic Lymphocytic Leukemia Research
Papers in
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- Lymphoma Diagnosis and Treatment 3
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- Ubiquitin and proteasome pathways 1
- Gene expression and cancer classification 1
- Cancer-related gene regulation 1
- Advanced Biosensing Techniques and Applications 1
- Co-authors
- T. Andrew Lister (4 shared papers)A. J. Norton (3 shared papers)Ken N. Ross (1 shared paper)Andrew P. Weng (1 shared paper)Todd R. Golub (1 shared paper)Jeffery L. Kutok (1 shared paper)Donna Neuberg (1 shared paper)Margaret A. Shipp (1 shared paper)
- Journals
- Journal of Clinical Oncology (2 papers)Nature Medicine (1 paper)British Journal of Haematology (1 paper)Hematology (1 paper)PubMed (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Kim Last
6 papers receiving 2.0k citations
Kim Last's Hit Papers
Peers
Comparison fields: 5 of 117
- Pathology and Forensic Medicine 665
- Genetics 281
- Molecular Biology 1.0k
- Oncology 373
- Cancer Research 166
Countries citing papers authored by Kim Last
This map shows the geographic impact of Kim Last'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 Kim Last with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kim Last more than expected).
Fields of papers citing papers by Kim Last
This network shows the impact of papers produced by Kim Last. 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 Kim Last. The network helps show where Kim Last may publish in the future.
Co-authors
The 25 scholars most cited alongside Kim Last, 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 | Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning Hit paper breakdown → | 2002 | 1855 |
| 2 | 2006 | 115 | |
| 3 | 2003 | 36 | |
| 4 | 2007 | 13 | |
| 5 | 2005 | 2 | |
| 6 | 2012 | 1 |
About Kim Last
Kim Last is a scholar working on Pathology and Forensic Medicine, Molecular Biology, Pulmonary and Respiratory Medicine, Oncology and Genetics, having authored 6 papers that have together received 2.0k indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (3 papers), Sarcoma Diagnosis and Treatment (1 paper), Multiple and Secondary Primary Cancers (1 paper), Viral-associated cancers and disorders (1 paper), Ubiquitin and proteasome pathways (1 paper), Gene expression and cancer classification (1 paper), Cancer-related gene regulation (1 paper) and Advanced Biosensing Techniques and Applications (1 paper). The work is most often cited by research in Pathology and Forensic Medicine (665 citations), Genetics (281 citations), Molecular Biology (1.0k citations), Oncology (373 citations) and Cancer Research (166 citations). Kim Last has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include T. Andrew Lister, A. J. Norton, Ken N. Ross, Andrew P. Weng, Todd R. Golub, Jeffery L. Kutok, Donna Neuberg, Margaret A. Shipp, Jill P. Mesirov and Eric S. Lander. Their work appears in journals such as Journal of Clinical Oncology, Nature Medicine, British Journal of Haematology, Hematology and PubMed.
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.