Marc Nasoff

1.7k citations
34 papers · 1.4k · h-index 16

Impact in

  • Hepatology top 2%
    • Hepatitis C virus research
  • Genetics top 5%
    • Hemoglobinopathies and Related Disorders

Papers in

Marc Nasoff

34 papers receiving 1.4k citations

Peers

Marc Nasoff
Comparison fields: 5 of 81
  • Hepatology 433
  • Genetics 180
  • Hematology 190
  • Epidemiology 329
  • Radiology, Nuclear Medicine and Imaging 200
Replace Urania Georgopoulou with:
Urania Georgopoulou Greece
Peter J. Welch United States
H. Claeys Belgium
Nadine Weich United States
Diletta Laccabue Italy
Vicky M.-H. Sung United States
Richard R. Gontarek United States
Gessica Filocamo Italy
Sean G. Buchanan United States
Wade Diehl United States
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Citations per field
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Urania Georgopoulou · 1×
Citations per year

Countries citing papers authored by Marc Nasoff

Since Specialization
Citations

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

Fields of papers citing papers by Marc Nasoff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marc Nasoff. 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 Marc Nasoff. The network helps show where Marc Nasoff may publish in the future.

Co-authors

The 25 scholars most cited alongside Marc Nasoff, 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 Marc Nasoff Line = papers co-authored together Marc Nasoff links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1991247
2 2015232
3 2004131
4 1991111
5 200491
6 200587
7 199176
8 200860
9 198456
10 200954
11 198447
12 201543
13 199326
14 198524
15 198023
16 200815
17 201314
18 202212
19 20009
20 20219

About Marc Nasoff

Marc Nasoff is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Immunology, Oncology and Genetics, having authored 34 papers that have together received 1.4k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (11 papers), Immunotherapy and Immune Responses (6 papers), Glycosylation and Glycoproteins Research (5 papers), Cell death mechanisms and regulation (5 papers), Hepatitis C virus research (4 papers), CAR-T cell therapy research (4 papers), RNA and protein synthesis mechanisms (4 papers) and Bacterial Genetics and Biotechnology (4 papers). The work is most often cited by research in Hepatology (433 citations), Genetics (180 citations), Hematology (190 citations), Epidemiology (329 citations) and Radiology, Nuclear Medicine and Imaging (200 citations). Marc Nasoff has collaborated with scholars based in United States, Japan and China. Frequent co-authors include Geneviève Inchauspé, S L Zebedee, Quinn L. Deveraux, Deborah Knee, A. M. Prince, Masahiko Sugitani, Kim Quon, A. M. Prince, Richard E. Wolf and Xin Du. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology, Cancer Research, Gene and Molecular Biology of the 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.

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