Tina Solvik

695 citations
5 papers · 493 · 1 hit paper · h-index 4

Impact in

Papers in

    • CRISPR and Genetic Engineering 2
    • Extracellular vesicles in disease 2
    • RNA Research and Splicing 1
    • Autophagy in Disease and Therapy 3

Tina Solvik

5 papers receiving 486 citations

Tina Solvik's Hit Papers

The LC3-conjugation machinery specifies the loading of RNA-binding proteins into extracellular vesicles 2020 · 349 citations
3490+2+4Years since publication100200300

Peers

Tina Solvik
Comparison fields: 5 of 62
  • Physiology 41
  • Cancer Research 122
  • Epidemiology 203
  • Molecular Biology 335
  • Cell Biology 78
Replace Robert Grabski with:
Robert Grabski United States
Thiago Castro‐Gomes Brazil
Subhash B. Arya India
Fengyu Wang China
Christina Begon‐Pescia France
Manuel Alonso Y Adell Austria
Nimisha Sharma India
Kimberly K. Kajihara United States
Richard Silva Brazil
Joanne Whitehead United States
Tina Solvik relative to Robert Grabski United States Robert Grabski's profile →
Citations per field
00.5×10×13.1×
Robert Grabski · 1×
Citations per year

Countries citing papers authored by Tina Solvik

Since Specialization
Citations

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

Fields of papers citing papers by Tina Solvik

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Tina Solvik, 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 Tina Solvik Line = papers co-authored together Tina Solvik links everyone, so they are left out of the graph.

All Works

5 of 5 papers shown
#Work
1
The LC3-conjugation machinery specifies the loading of RNA-binding proteins into extracellular vesicles
Hit paper breakdown →
2020349
2 2022100
3 202039
4 20164
5
Endolysosomal inhibition induces the autophagy-dependent secretion of autophagosomal cargo
20201

About Tina Solvik

Tina Solvik is a scholar working on Molecular Biology, Epidemiology, Ecology, Public Health, Environmental and Occupational Health and Physiology, having authored 5 papers that have together received 493 indexed citations. Recurring topics across this work include Autophagy in Disease and Therapy (3 papers), CRISPR and Genetic Engineering (2 papers), Extracellular vesicles in disease (2 papers), Mosquito-borne diseases and control (1 paper), Vibrio bacteria research studies (1 paper), RNA Research and Splicing (1 paper), Calcium signaling and nucleotide metabolism (1 paper) and Bacteriophages and microbial interactions (1 paper). The work is most often cited by research in Physiology (41 citations), Cancer Research (122 citations), Epidemiology (203 citations), Molecular Biology (335 citations) and Cell Biology (78 citations). Tina Solvik has collaborated with scholars based in United States, India and China. Frequent co-authors include Jayanta Debnath, Eric J. Huang, Andrew M. Leidal, Timothy Marsh, Arun P. Wiita, Hani Goodarzi, Dachuan Zhang, Hector H. Huang, FuiBoon Kai and Jennifer Y. Liu. Their work appears in journals such as The Journal of Cell Biology, Nature Cell Biology, Nature Microbiology and eScholarship (California Digital Library).

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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