Michael Lovci
Impact in
- Aging top 2%
- Cancer Research top 2%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
Papers in
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- RNA Research and Splicing 9
- RNA and protein synthesis mechanisms 4
- RNA modifications and cancer 4
- CRISPR and Genetic Engineering 2
- Single-cell and spatial transcriptomics 2
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- MicroRNA in disease regulation 4
- Cancer Genomics and Diagnostics 2
- Co-authors
- G Yeo (10 shared papers)Amy E. Pasquinelli (2 shared papers)James P. Broughton (1 shared paper)Tiffany Y Liang (3 shared papers)María Morell (1 shared paper)Grace E. Peng (1 shared paper)Yangling Mu (1 shared paper)Fred H. Gage (1 shared paper)
- Journals
- Molecular Cell (3 papers)Blood (2 papers)Nature Structural & Molecular Biology (2 papers)PLoS Genetics (1 paper)Advances in experimental medicine and biology (1 paper)
- Partner nations
- United StatesSingaporeBrazil
In The Last Decade
Michael Lovci
16 papers receiving 2.1k citations
Michael Lovci's Hit Papers
Peers
Comparison fields: 5 of 89
- Aging 107
- Cancer Research 689
- Molecular Biology 1.7k
- Plant Science 418
- Genetics 254
Countries citing papers authored by Michael Lovci
This map shows the geographic impact of Michael Lovci'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 Michael Lovci with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Lovci more than expected).
Fields of papers citing papers by Michael Lovci
This network shows the impact of papers produced by Michael Lovci. 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 Michael Lovci. The network helps show where Michael Lovci may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Lovci, 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 | L1 retrotransposition in human neural progenitor cells Hit paper breakdown → | 2009 | 654 |
| 2 | 2016 | 353 | |
| 3 | 2013 | 261 | |
| 4 | 2010 | 250 | |
| 5 | 2012 | 217 | |
| 6 | 2017 | 126 | |
| 7 | 2008 | 82 | |
| 8 | 2009 | 45 | |
| 9 | 2018 | 41 | |
| 10 | 2013 | 36 | |
| 11 | 2016 | 35 | |
| 12 | 2018 | 21 | |
| 13 | 2021 | 3 | |
| 14 | 2011 | 3 | |
| 15 | 2014 | 1 | |
| 16 | 2014 | 1 | |
| 17 | 2021 | 0 |
About Michael Lovci
Michael Lovci is a scholar working on Molecular Biology, Cancer Research, Aging, Paleontology and Oceanography, having authored 17 papers that have together received 2.1k indexed citations. Recurring topics across this work include RNA Research and Splicing (9 papers), RNA and protein synthesis mechanisms (4 papers), MicroRNA in disease regulation (4 papers), RNA modifications and cancer (4 papers), Cancer Genomics and Diagnostics (2 papers), CRISPR and Genetic Engineering (2 papers), Genetics, Aging, and Longevity in Model Organisms (2 papers) and Single-cell and spatial transcriptomics (2 papers). The work is most often cited by research in Aging (107 citations), Cancer Research (689 citations), Molecular Biology (1.7k citations), Plant Science (418 citations) and Genetics (254 citations). Michael Lovci has collaborated with scholars based in United States, Singapore and Brazil. Frequent co-authors include G Yeo, Amy E. Pasquinelli, James P. Broughton, Tiffany Y Liang, María Morell, Grace E. Peng, Yangling Mu, Fred H. Gage, José L. García-Pérez and John V. Moran. Their work appears in journals such as Molecular Cell, Blood, Nature Structural & Molecular Biology, PLoS Genetics and Advances in experimental medicine and 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.