Eric G. Moss

5.9k citations
34 papers · 4.6k indexed · 2 hit papers · h-index 26

Eric G. Moss

32 papers receiving 4.5k citations

Hit Papers

Expression profiling of mammalian microRNAs uncovers a su...1.3k19972026200620164008001.2k

Peers

Eric G. Moss
Comparison fields: 5 of 115
  • Aging 588
  • Cancer Research 2.3k
  • Molecular Biology 3.6k
  • Developmental Neuroscience 153
  • Endocrine and Autonomic Systems 117
Replace Mariana Lagos‐Quintana with:
Mariana Lagos‐Quintana United States
Yin C. Lin United States
Scott Kuersten United States
Eric Bertolino United States
Jason X. Cheng United States
Dimos Gaidatzis Switzerland
Concepción Rodrı́guez Esteban United States
Bruce Wightman United States
Yanfang Fu United States
Paul G. Giresi United States
Eric G. Moss relative to Mariana Lagos‐Quintana United States Mariana Lagos‐Quintana's profile →
Citations per field
00.5×5.3×
Mariana Lagos‐Quintana · 1×
Citations per year

Countries citing papers authored by Eric G. Moss

Since Specialization
Citations

This map shows the geographic impact of Eric G. Moss'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 Eric G. Moss with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric G. Moss more than expected).

Fields of papers citing papers by Eric G. Moss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric G. Moss. 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 Eric G. Moss. The network helps show where Eric G. Moss may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Eric G. Moss, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Eric G. Moss Line = papers co-authored together Eric G. Moss links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20230
3 202136
4 201595
5 20149
6 201386
7 201261
8 2007153
9 2007153
10 2007236
11 2003266
12 200366
13 2003151
14 20036
15 200290
16 200225
17 200142
18 200030
19
The Cold Shock Domain Protein LIN-28 Controls Developmental Timing in C. elegans and Is Regulated by the lin-4 RNAbreakdown →
1997688
20 199459

About Eric G. Moss

Eric G. Moss is a scholar working on Aging, Cancer Research, Molecular Biology, Plant Science and Cardiology and Cardiovascular Medicine, having authored 34 papers that have together received 4.6k indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (16 papers), RNA Research and Splicing (13 papers), MicroRNA in disease regulation (9 papers), RNA modifications and cancer (5 papers), CRISPR and Genetic Engineering (5 papers), Viral Infections and Immunology Research (4 papers), RNA Interference and Gene Delivery (4 papers) and Photosynthetic Processes and Mechanisms (4 papers). The work is most often cited by research in Aging (588 citations), Cancer Research (2.3k citations), Molecular Biology (3.6k citations), Developmental Neuroscience (153 citations) and Endocrine and Autonomic Systems (117 citations). Eric G. Moss has collaborated with scholars based in United States, Canada and Ireland. Frequent co-authors include Victor Ambros, Lingjuan Tang, Rosalind C. Lee, Ethan Dmitrovsky, Lorenzo F. Sempere, Sarah J. Freemantle, Ian Pitha, Vincent R. Racaniello, Dong‐Hua Yang and Ruibao Ren. Their work appears in journals such as Current Biology, Genetics, Development, Stem Cells and RNA 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.

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