Daniel S. Lieber
Impact in
- Clinical Biochemistry top 2%
- Metabolism and Genetic Disorders
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Cancer Genomics and Diagnostics
Papers in
-
- Cancer Genomics and Diagnostics 6
-
- Mitochondrial Function and Pathology 2
- Peroxisome Proliferator-Activated Receptors 1
- Co-authors
- Reut Shalgi (1 shared paper)Moshe Oren (1 shared paper)Yitzhak Pilpel (1 shared paper)Vamsi K. Mootha (4 shared papers)Sarah E. Calvo (4 shared papers)Steven G. Hershman (3 shared papers)Shangtao Liu (3 shared papers)David R. Thorburn (2 shared papers)
- Journals
- Annals of Oncology (2 papers)Cancer Research (2 papers)Clinical Cancer Research (1 paper)Neurology (1 paper)PLoS Computational Biology (1 paper)
- Partner nations
- United StatesHong KongAustralia
In The Last Decade
Daniel S. Lieber
17 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 102
- Clinical Biochemistry 209
- Cancer Research 340
- Molecular Biology 786
- Industrial and Manufacturing Engineering 59
- Oncology 106
Countries citing papers authored by Daniel S. Lieber
This map shows the geographic impact of Daniel S. Lieber'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 S. Lieber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel S. Lieber more than expected).
Fields of papers citing papers by Daniel S. Lieber
This network shows the impact of papers produced by Daniel S. Lieber. 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 S. Lieber. The network helps show where Daniel S. Lieber may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel S. Lieber, 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 | 2007 | 414 | |
| 2 | 2012 | 346 | |
| 3 | 2013 | 117 | |
| 4 | 2013 | 84 | |
| 5 | 2017 | 62 | |
| 6 | 2014 | 35 | |
| 7 | 2021 | 30 | |
| 8 | 2018 | 28 | |
| 9 | 2010 | 27 | |
| 10 | 2012 | 25 | |
| 11 | 2017 | 14 | |
| 12 | 2016 | 11 | |
| 13 | 2018 | 11 | |
| 14 | 2017 | 3 | |
| 15 | 2013 | 3 | |
| 16 | 2012 | 2 | |
| 17 | 2017 | 1 |
About Daniel S. Lieber
Daniel S. Lieber is a scholar working on Cancer Research, Molecular Biology, Oncology, Control and Systems Engineering and Genetics, having authored 17 papers that have together received 1.2k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (6 papers), Cancer Immunotherapy and Biomarkers (5 papers), Genomics and Rare Diseases (2 papers), Pancreatic and Hepatic Oncology Research (2 papers), Mitochondrial Function and Pathology (2 papers), Fault Detection and Control Systems (2 papers), CAR-T cell therapy research (2 papers) and Peroxisome Proliferator-Activated Receptors (1 paper). The work is most often cited by research in Clinical Biochemistry (209 citations), Cancer Research (340 citations), Molecular Biology (786 citations), Industrial and Manufacturing Engineering (59 citations) and Oncology (106 citations). Daniel S. Lieber has collaborated with scholars based in United States, Hong Kong and Australia. Frequent co-authors include Reut Shalgi, Moshe Oren, Yitzhak Pilpel, Vamsi K. Mootha, Sarah E. Calvo, Steven G. Hershman, Shangtao Liu, David R. Thorburn, David B. Jaffe and Jack Goldblatt. Their work appears in journals such as Annals of Oncology, Cancer Research, Clinical Cancer Research, Neurology and PLoS Computational Biology.
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.