Sherman M. Weissman
- Geriatrics and Gerontology top 0.2%
- Molecular Biology top 0.2%
- Genomics and Chromatin Dynamics 33
- RNA and protein synthesis mechanisms 31
- CRISPR and Genetic Engineering 20
- RNA modifications and cancer 20
- RNA Research and Splicing 20
- RNA Interference and Gene Delivery 18
- Epigenetics and DNA Methylation 18
- Cancer Research top 0.5%
- Genetics top 0.5%
- Genetics top 1%
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- Bacteriophages and microbial interactions 20
- Co-authors
- M SnyderMark GersteinBernard G. ForgetFrancis S. CollinsAlexander E. UrbanJoel RozowskyPeter E. NewburgerPaul Bertone
- Partner nations
- United StatesChinaJapan
In The Last Decade
Sherman M. Weissman
222 papers receiving 14.8k citations
Hit Papers
Peers
Comparison fields: 5 of 177
- Geriatrics and Gerontology 728
- Molecular Biology 11.1k
- Cancer Research 2.3k
- Genetics 2.7k
- Genetics 887
Countries citing papers authored by Sherman M. Weissman
This map shows the geographic impact of Sherman M. Weissman'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 Sherman M. Weissman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sherman M. Weissman more than expected).
Fields of papers citing papers by Sherman M. Weissman
This network shows the impact of papers produced by Sherman M. Weissman. 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 Sherman M. Weissman. The network helps show where Sherman M. Weissman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sherman M. Weissman, 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 | 2022 | 24 | |
| 2 | 2019 | 11 | |
| 3 | 2015 | 110 | |
| 4 | 2014 | 137 | |
| 5 | 2012 | 63 | |
| 6 | 2010 | 150 | |
| 7 | 2010 | 423 | |
| 8 | 2009 | 43 | |
| 9 | 2008 | 172 | |
| 10 | 2007 | 20 | |
| 11 | 2004 | 140 | |
| 12 | 2002 | 136 | |
| 13 | cDNA preparation and characterization | 1999 | 2 |
| 14 | 1992 | 72 | |
| 15 | 1981 | 2 | |
| 16 | Red Cell Metabolism. A Manual of Biochemical Methods. 2nd Edition | 1976 | 29 |
| 17 | Oxygen Affinity of Hemoglobin and Red Cell Acid Base Status | 1974 | 269 |
| 18 | Techniques in Protein Biosynthesis | 1970 | 1 |
| 19 | 1966 | 1 | |
| 20 | Pseudouridine metabolism. II. Urinary excretion in gout, psoriasis, leukemia, and heterozygous oroticaciduria. | 1962 | 29 |
About Sherman M. Weissman
Sherman M. Weissman is a scholar working on Molecular Biology, Genetics and Immunology, having authored 224 papers that have together received 15.5k indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (33 papers), RNA and protein synthesis mechanisms (31 papers), CRISPR and Genetic Engineering (20 papers), Bacteriophages and microbial interactions (20 papers), RNA modifications and cancer (20 papers), RNA Research and Splicing (20 papers), RNA Interference and Gene Delivery (18 papers) and Epigenetics and DNA Methylation (18 papers). The work is most often cited by research in Geriatrics and Gerontology (728 citations), Molecular Biology (11.1k citations) and Cancer Research (2.3k citations). Sherman M. Weissman has collaborated with scholars based in United States, China and Japan. Frequent co-authors include M Snyder, Mark Gerstein, Bernard G. Forget, Francis S. Collins, Alexander E. Urban, Joel Rozowsky, Peter E. Newburger, Paul Bertone, Thomas Royce and Pudur Jagadeeswaran.
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.