Kimberly Umans

16 total papers · 750 total citations
12 papers, 569 citations indexed

About

Kimberly Umans is a scholar working on Pathology and Forensic Medicine, Immunology and Molecular Biology. According to data from OpenAlex, Kimberly Umans has authored 12 papers receiving a total of 569 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Pathology and Forensic Medicine, 4 papers in Immunology and 3 papers in Molecular Biology. Recurrent topics in Kimberly Umans's work include Multiple Sclerosis Research Studies (5 papers), Immunotherapy and Immune Responses (4 papers) and Rheumatoid Arthritis Research and Therapies (3 papers). Kimberly Umans is often cited by papers focused on Multiple Sclerosis Research Studies (5 papers), Immunotherapy and Immune Responses (4 papers) and Rheumatoid Arthritis Research and Therapies (3 papers). Kimberly Umans collaborates with scholars based in United States, United Kingdom and Czechia. Kimberly Umans's co-authors include Samantha Budd Haeberlein, Patrick Burkett, Ying Tian, Jerome Barakos, Karen Smirnakis, Spyros Chalkias, Derk D. Purcell, Priya Singhal, Stephen Salloway and Guanfang Wang and has published in prestigious journals such as Neurology, Journal of Thrombosis and Haemostasis and JAMA Neurology.

In The Last Decade

Kimberly Umans

11 papers receiving 561 citations

Hit Papers

Amyloid-Related Imaging A... 2021 2026 2022 2024 2021 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
Kimberly Umans 295 108 104 104 103 12 569
Kenneth C. Dole 306 1.0× 61 0.6× 174 1.7× 124 1.2× 126 1.2× 7 638
Priya Singhal 314 1.1× 141 1.3× 124 1.2× 104 1.0× 30 0.3× 15 544
Hong Zhu 203 0.7× 45 0.4× 116 1.1× 29 0.3× 100 1.0× 15 503
Françoise Gerber 347 1.2× 122 1.1× 128 1.2× 83 0.8× 22 0.2× 7 553
Robert M. Crescentini 419 1.4× 84 0.8× 187 1.8× 60 0.6× 15 0.1× 13 646
Harry Twaalfhoven 164 0.6× 25 0.2× 162 1.6× 85 0.8× 145 1.4× 15 560
Qian Wu 316 1.1× 34 0.3× 139 1.3× 55 0.5× 15 0.1× 15 628
Ronan Pendu 295 1.0× 46 0.4× 135 1.3× 54 0.5× 11 0.1× 7 689
Susan H. Lee 340 1.2× 37 0.3× 288 2.8× 36 0.3× 24 0.2× 10 683
Guoda Ma 281 1.0× 36 0.3× 210 2.0× 31 0.3× 34 0.3× 15 538

Countries citing papers authored by Kimberly Umans

Since Specialization
Citations

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

Fields of papers citing papers by Kimberly Umans

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kimberly Umans

This figure shows the co-authorship network connecting the top 25 collaborators of Kimberly Umans. A scholar is included among the top collaborators of Kimberly Umans 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 Kimberly Umans. Kimberly Umans 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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