Mario R. Capecchi
- Molecular Biology top 0.05%
- Developmental Biology and Gene Regulation 48
- CRISPR and Genetic Engineering 42
- Pluripotent Stem Cells Research 27
- Congenital heart defects research 24
- RNA and protein synthesis mechanisms 16
- RNA Interference and Gene Delivery 14
- Genetics top 0.05%
- Animal Genetics and Reproduction 37
- Developmental Biology top 0.5%
- Developmental Neuroscience top 0.5%
- Aging top 1%
-
- Sarcoma Diagnosis and Treatment 20
- Co-authors
- Kirk R. ThomasEugenio SangiorgiSuzanne L. MansourNancy R. ManleyJudy M. GoddardDeneen M. WellikChu‐Xia DengAnne M. Boulet
- Partner nations
- United StatesBelgiumChina
In The Last Decade
Mario R. Capecchi
238 papers receiving 27.4k citations
Hit Papers
Peers
Comparison fields: 5 of 184
- Molecular Biology 20.4k
- Genetics 7.5k
- Developmental Biology 405
- Developmental Neuroscience 750
- Aging 260
Countries citing papers authored by Mario R. Capecchi
This map shows the geographic impact of Mario R. Capecchi'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 Mario R. Capecchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mario R. Capecchi more than expected).
Fields of papers citing papers by Mario R. Capecchi
This network shows the impact of papers produced by Mario R. Capecchi. 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 Mario R. Capecchi. The network helps show where Mario R. Capecchi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mario R. Capecchi, 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 | 2025 | 1 | |
| 2 | 2023 | 2 | |
| 3 | 2020 | 3 | |
| 4 | 2020 | 6 | |
| 5 | 2015 | 71 | |
| 6 | 2013 | 57 | |
| 7 | The intestinal stem cell markers Bmi1 and Lgr5 identify two functionally distinct populationsbreakdown → | 2011 | 634 |
| 8 | 2011 | 43 | |
| 9 | 2009 | 58 | |
| 10 | 2008 | 62 | |
| 11 | 2006 | 156 | |
| 12 | 2006 | 1 | |
| 13 | 2004 | 164 | |
| 14 | 2002 | 166 | |
| 15 | 1997 | 103 | |
| 16 | Mice lacking angiotensin-converting enzyme have low blood pressure, renal pathology, and reduced male fertility.breakdown → | 1996 | 380 |
| 17 | A mouse model for the delta F508 allele of cystic fibrosis.breakdown → | 1995 | 249 |
| 18 | Molecular genetics of early Drosophila and mouse development | 1989 | 5 |
| 19 | 1985 | 22 | |
| 20 | 1975 | 1 |
About Mario R. Capecchi
Mario R. Capecchi is a scholar working on Molecular Biology, Genetics and Cellular and Molecular Neuroscience, having authored 239 papers that have together received 28.3k indexed citations. Recurring topics across this work include Developmental Biology and Gene Regulation (48 papers), CRISPR and Genetic Engineering (42 papers), Animal Genetics and Reproduction (37 papers), Pluripotent Stem Cells Research (27 papers), Congenital heart defects research (24 papers), Sarcoma Diagnosis and Treatment (20 papers), RNA and protein synthesis mechanisms (16 papers) and RNA Interference and Gene Delivery (14 papers). The work is most often cited by research in Molecular Biology (20.4k citations), Genetics (7.5k citations) and Developmental Biology (405 citations). Mario R. Capecchi has collaborated with scholars based in United States, Belgium and China. Frequent co-authors include Kirk R. Thomas, Eugenio Sangiorgi, Suzanne L. Mansour, Nancy R. Manley, Judy M. Goddard, Deneen M. Wellik, Chu‐Xia Deng, Anne M. Boulet, Anne Moon and Brian G. Condie. Their work appears in journals such as Nature, Science and Cell.
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.