M.G. Byers

4.5k citations
54 papers · 3.3k · h-index 28

Impact in

Papers in

    • Glycosylation and Glycoproteins Research 11
    • RNA modifications and cancer 6
    • RNA Research and Splicing 4
    • Genetics and Neurodevelopmental Disorders 6
    • Animal Genetics and Reproduction 4

M.G. Byers

52 papers receiving 3.2k citations

Peers

M.G. Byers
Comparison fields: 5 of 110
  • Immunology and Allergy 339
  • Molecular Biology 1.8k
  • Nephrology 177
  • Endocrinology, Diabetes and Metabolism 357
  • Biochemistry 160
Replace L. Marty with:
L. Marty France
Ph. Jeanteur France
Senén Vilaró Spain
T.B. Shows United States
Jean‐Dominique Vassalli Switzerland
Richard M. Rohan United States
Kazue Hattori United States
Takahiko Hara Japan
Terri Davis-Smyth United States
Dennis K. Watson United States
M.G. Byers relative to L. Marty France L. Marty's profile →
Citations per field
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L. Marty · 1×
Citations per year

Countries citing papers authored by M.G. Byers

Since Specialization
Citations

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

Fields of papers citing papers by M.G. Byers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1988376
2 1988375
3 1990319
4 1990283
5 1989275
6 1993119
7 1992117
8 199498
9 198490
10
Interleukin-1 gene (IL1) assigned to long arm of human chromosome 2.
198686
11 199483
12 198980
13 198975
14 199274
15 198872
16 199066
17 198762
18 199051
19 199246
20 199143

About M.G. Byers

M.G. Byers is a scholar working on Molecular Biology, Genetics, Immunology, Immunology and Allergy and Surgery, having authored 54 papers that have together received 3.3k indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (11 papers), Cell Adhesion Molecules Research (7 papers), Genetics and Neurodevelopmental Disorders (6 papers), RNA modifications and cancer (6 papers), Pancreatic function and diabetes (5 papers), RNA Research and Splicing (4 papers), Peptidase Inhibition and Analysis (4 papers) and Animal Genetics and Reproduction (4 papers). The work is most often cited by research in Immunology and Allergy (339 citations), Molecular Biology (1.8k citations), Nephrology (177 citations), Endocrinology, Diabetes and Metabolism (357 citations) and Biochemistry (160 citations). M.G. Byers has collaborated with scholars based in United States, Finland and Japan. Frequent co-authors include Roger L. Eddy, T.B. Shows, T.B. Shows, Hirofumi Fukumoto, Thomas B. Shows, Yoshimitsu Fukushima, T. Kayano, Susumu Seino, Graeme I. Bell and G I Bell. Their work appears in journals such as Genomics, Journal of Biological Chemistry, Proceedings of the National Academy of Sciences, Diabetes and Molecular Endocrinology.

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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