Rob Moccia
Impact in
Papers in
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- Machine Learning in Bioinformatics 1
- RNA and protein synthesis mechanisms 1
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- Amyotrophic Lateral Sclerosis Research 4
- Parkinson's Disease Mechanisms and Treatments 1
- Co-authors
- Kevin Eggan (4 shared papers)Daniel A. Mordes (3 shared papers)Aaron Burberry (2 shared papers)Brandi N. Davis‐Dusenbery (2 shared papers)Francesco Limone (2 shared papers)Joseph R. Klim (2 shared papers)Kanchana K. Gamage (1 shared paper)Kuchuan Chen (1 shared paper)
- Journals
- Nature Neuroscience (2 papers)Acta Neuropathologica Communications (1 paper)Human Genetics and Genomics Advances (1 paper)Science Translational Medicine (1 paper)Bioinformatics (1 paper)
- Partner nations
- United StatesNetherlandsUnited Kingdom
In The Last Decade
Rob Moccia
8 papers receiving 625 citations
Rob Moccia's Hit Papers
Peers
Comparison fields: 5 of 54
- Neurology 486
- Genetics 312
- Neurology 94
- Molecular Biology 334
- Cellular and Molecular Neuroscience 79
Countries citing papers authored by Rob Moccia
This map shows the geographic impact of Rob Moccia'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 Rob Moccia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rob Moccia more than expected).
Fields of papers citing papers by Rob Moccia
This network shows the impact of papers produced by Rob Moccia. 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 Rob Moccia. The network helps show where Rob Moccia may publish in the future.
Co-authors
The 25 scholars most cited alongside Rob Moccia, 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 | ALS-implicated protein TDP-43 sustains levels of STMN2, a mediator of motor neuron growth and repair Hit paper breakdown → | 2019 | 345 |
| 2 | 2016 | 188 | |
| 3 | 2013 | 56 | |
| 4 | 2018 | 20 | |
| 5 | 2023 | 13 | |
| 6 | 2025 | 2 | |
| 7 | 2000 | 2 | |
| 8 | 2022 | 1 | |
| 9 | 2025 | 0 |
About Rob Moccia
Rob Moccia is a scholar working on Molecular Biology, Neurology, Genetics, Cardiology and Cardiovascular Medicine and Cellular and Molecular Neuroscience, having authored 9 papers that have together received 627 indexed citations. Recurring topics across this work include Amyotrophic Lateral Sclerosis Research (4 papers), Cardiomyopathy and Myosin Studies (3 papers), Neurogenetic and Muscular Disorders Research (3 papers), Cardiovascular Effects of Exercise (2 papers), Machine Learning in Bioinformatics (1 paper), Alzheimer's disease research and treatments (1 paper), RNA and protein synthesis mechanisms (1 paper) and Parkinson's Disease Mechanisms and Treatments (1 paper). The work is most often cited by research in Neurology (486 citations), Genetics (312 citations), Neurology (94 citations), Molecular Biology (334 citations) and Cellular and Molecular Neuroscience (79 citations). Rob Moccia has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Kevin Eggan, Daniel A. Mordes, Aaron Burberry, Brandi N. Davis‐Dusenbery, Francesco Limone, Joseph R. Klim, Kanchana K. Gamage, Kuchuan Chen, Seth H. Cassel and Irune Guerra San Juan. Their work appears in journals such as Nature Neuroscience, Acta Neuropathologica Communications, Human Genetics and Genomics Advances, Science Translational Medicine and Bioinformatics.
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.