Jan Attig

3.6k citations
28 papers · 2.0k · h-index 19

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
  • Neurology top 5%
    • Amyotrophic Lateral Sclerosis Research

Papers in

    • RNA Research and Splicing 13
    • RNA and protein synthesis mechanisms 7
    • RNA modifications and cancer 7
    • RNA regulation and disease 4
    • Immune Cell Function and Interaction 4
    • Immunotherapy and Immune Responses 4
    • T-cell and B-cell Immunology 3

Jan Attig

27 papers receiving 2.0k citations

Peers

Jan Attig
Comparison fields: 5 of 94
  • Cancer Research 405
  • Neurology 346
  • Genetics 233
  • Molecular Biology 1.5k
  • Immunology 223
Replace Zhenbao Yu with:
Zhenbao Yu Canada
Elisa Caffarelli Italy
Sarah Tisdale United States
Lynne Lacomis United States
Shuning He United States
Jessica E. Hutti United States
Thomas Schwarzl Germany
Tal Teitz United States
Kimberly A. Dittmar United States
Alistair M. Chalk Australia
Jan Attig relative to Zhenbao Yu Canada Zhenbao Yu's profile →
Citations per field
00.5×3.1×
Zhenbao Yu · 1×
Citations per year

Countries citing papers authored by Jan Attig

Since Specialization
Citations

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

Fields of papers citing papers by Jan Attig

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013378
2 2013312
3 2011287
4 2021129
5 2015117
6 201499
7 201898
8 201784
9 201974
10 202066
11 201761
12 201650
13 201948
14 201841
15 201834
16 201728
17 201619
18 202319
19 201618
20 201917

About Jan Attig

Jan Attig is a scholar working on Molecular Biology, Immunology, Plant Science, Cancer Research and Epidemiology, having authored 28 papers that have together received 2.0k indexed citations. Recurring topics across this work include RNA Research and Splicing (13 papers), RNA and protein synthesis mechanisms (7 papers), RNA modifications and cancer (7 papers), Immune Cell Function and Interaction (4 papers), Immunotherapy and Immune Responses (4 papers), RNA regulation and disease (4 papers), T-cell and B-cell Immunology (3 papers) and Chromosomal and Genetic Variations (3 papers). The work is most often cited by research in Cancer Research (405 citations), Neurology (346 citations), Genetics (233 citations), Molecular Biology (1.5k citations) and Immunology (223 citations). Jan Attig has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Jernej Ule, Julian König, George Kassiotis, Hansruedi Mathys, Witold Filipowicz, Marina Chekulaeva, Roy Parker, Christopher R. Sibley, Ina Huppertz and George R. Young. Their work appears in journals such as eLife, Genome biology, Cell, Nature Genetics and Methods.

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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