Getnet Midekessa

16 total papers · 684 total citations
13 papers, 492 citations indexed

About

Getnet Midekessa is a scholar working on Molecular Biology, Immunology and Obstetrics and Gynecology. According to data from OpenAlex, Getnet Midekessa has authored 13 papers receiving a total of 492 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 5 papers in Immunology and 3 papers in Obstetrics and Gynecology. Recurrent topics in Getnet Midekessa's work include Extracellular vesicles in disease (12 papers), Reproductive System and Pregnancy (5 papers) and MicroRNA in disease regulation (3 papers). Getnet Midekessa is often cited by papers focused on Extracellular vesicles in disease (12 papers), Reproductive System and Pregnancy (5 papers) and MicroRNA in disease regulation (3 papers). Getnet Midekessa collaborates with scholars based in Estonia, Poland and United Kingdom. Getnet Midekessa's co-authors include Alireza Fazeli, Keerthie Dissanayake, Freddy Lättekivi, Kasun Godakumara, Aneta Andronowska, Janeli Viil, Sourav Bhattacharjee, Toonika Rinken, Sergei Kopanchuk and James Ord and has published in prestigious journals such as International Journal of Molecular Sciences, Journal of Dairy Science and Frontiers in Plant Science.

In The Last Decade

Getnet Midekessa

12 papers receiving 491 citations

Hit Papers

Zeta Potential of Extrace... 2020 2026 2022 2024 2020 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Getnet Midekessa 351 122 98 91 48 13 492
Huanhuan Guo 145 0.4× 34 0.3× 86 0.9× 107 1.2× 38 0.8× 26 429
Geonhee Han 299 0.9× 132 1.1× 68 0.7× 36 0.4× 14 0.3× 18 440
Jing Cheng 197 0.6× 65 0.5× 77 0.8× 171 1.9× 28 0.6× 14 418
Hong Shi 302 0.9× 215 1.8× 27 0.3× 38 0.4× 20 0.4× 28 535
Na Yin 213 0.6× 64 0.5× 64 0.7× 43 0.5× 52 1.1× 17 457
Aaron J. Sorrin 179 0.5× 50 0.4× 56 0.6× 151 1.7× 39 0.8× 9 446
Xinyan Hao 215 0.6× 46 0.4× 120 1.2× 100 1.1× 48 1.0× 19 441
Raquel Pazos 410 1.2× 169 1.4× 101 1.0× 72 0.8× 36 0.8× 11 538
Ming Jia 225 0.6× 41 0.3× 103 1.1× 122 1.3× 59 1.2× 12 456
António Ramos-Fernández 336 1.0× 30 0.2× 104 1.1× 65 0.7× 19 0.4× 17 532

Countries citing papers authored by Getnet Midekessa

Since Specialization
Citations

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

Fields of papers citing papers by Getnet Midekessa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Getnet Midekessa

This figure shows the co-authorship network connecting the top 25 collaborators of Getnet Midekessa. A scholar is included among the top collaborators of Getnet Midekessa based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Getnet Midekessa. Getnet Midekessa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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