Que T. Lambert
Impact in
- Molecular Biology top 5%
- Protein Kinase Regulation and GTPase Signaling
- PI3K/AKT/mTOR signaling in cancer
- Immunology and Allergy top 5%
- Cell Adhesion Molecules Research
Papers in
- Co-authors
- Channing J. Der (12 shared papers)Gary W. Reuther (14 shared papers)John K. Westwick (3 shared papers)Marc H. Symons (2 shared papers)Richard G. Pestell (2 shared papers)Linda Van Aelst (1 shared paper)Michael A. Caligiuri (3 shared papers)John Sondek (2 shared papers)
- Journals
- Journal of Biological Chemistry (6 papers)Molecular and Cellular Biology (4 papers)Blood (2 papers)Biochemical Journal (2 papers)Molecular Cancer Therapeutics (1 paper)
- Partner nations
- United StatesNetherlandsCanada
In The Last Decade
Que T. Lambert
21 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 62
- Molecular Biology 1.1k
- Immunology and Allergy 62
- Oncology 211
- Cell Biology 108
- Genetics 65
Countries citing papers authored by Que T. Lambert
This map shows the geographic impact of Que T. Lambert'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 Que T. Lambert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Que T. Lambert more than expected).
Fields of papers citing papers by Que T. Lambert
This network shows the impact of papers produced by Que T. Lambert. 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 Que T. Lambert. The network helps show where Que T. Lambert may publish in the future.
Co-authors
The 25 scholars most cited alongside Que T. Lambert, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1997 | 396 | |
| 2 | 2002 | 274 | |
| 3 | 1996 | 131 | |
| 4 | 2001 | 108 | |
| 5 | 2000 | 107 | |
| 6 | 2001 | 103 | |
| 7 | 1999 | 102 | |
| 8 | 2002 | 82 | |
| 9 | 1998 | 81 | |
| 10 | 2004 | 60 | |
| 11 | 2007 | 54 | |
| 12 | 2017 | 48 | |
| 13 | 2008 | 47 | |
| 14 | 2018 | 44 | |
| 15 | 2015 | 34 | |
| 16 | 2010 | 27 | |
| 17 | 1998 | 25 | |
| 18 | 2010 | 23 | |
| 19 | 2011 | 8 | |
| 20 | 2006 | 6 |
About Que T. Lambert
Que T. Lambert is a scholar working on Genetics, Oncology, Molecular Biology, Hematology and Pathology and Forensic Medicine, having authored 22 papers that have together received 1.8k indexed citations. Recurring topics across this work include Protein Kinase Regulation and GTPase Signaling (10 papers), Cytokine Signaling Pathways and Interactions (4 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (4 papers), Acute Myeloid Leukemia Research (3 papers), PI3K/AKT/mTOR signaling in cancer (1 paper), Fibroblast Growth Factor Research (1 paper), Protein Degradation and Inhibitors (1 paper) and Cancer Mechanisms and Therapy (1 paper). The work is most often cited by research in Molecular Biology (1.1k citations), Immunology and Allergy (62 citations), Oncology (211 citations), Cell Biology (108 citations) and Genetics (65 citations). Que T. Lambert has collaborated with scholars based in United States, Netherlands and Canada. Frequent co-authors include Channing J. Der, Gary W. Reuther, John K. Westwick, Marc H. Symons, Richard G. Pestell, Linda Van Aelst, Michael A. Caligiuri, John Sondek, John G. Collard and David Peter Siderovski. Their work appears in journals such as Journal of Biological Chemistry, Molecular and Cellular Biology, Blood, Biochemical Journal and Molecular Cancer Therapeutics.
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.