Johanna Uusimaa

4.1k total citations
82 papers, 1.8k citations indexed

About

Johanna Uusimaa is a scholar working on Molecular Biology, Clinical Biochemistry and Genetics. According to data from OpenAlex, Johanna Uusimaa has authored 82 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Molecular Biology, 33 papers in Clinical Biochemistry and 16 papers in Genetics. Recurrent topics in Johanna Uusimaa's work include Mitochondrial Function and Pathology (37 papers), Metabolism and Genetic Disorders (33 papers) and ATP Synthase and ATPases Research (17 papers). Johanna Uusimaa is often cited by papers focused on Mitochondrial Function and Pathology (37 papers), Metabolism and Genetic Disorders (33 papers) and ATP Synthase and ATPases Research (17 papers). Johanna Uusimaa collaborates with scholars based in Finland, Sweden and Netherlands. Johanna Uusimaa's co-authors include Kari Majamaa, Reetta Hinttala, Heikki Rantala, Pirjo Isohanni, Ilmo E. Hassinen, Jukka Hakkola, Anne M. Remes, Leena Vainionpää, Helena Pihko and Niklas Darín and has published in prestigious journals such as Nature, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Johanna Uusimaa

75 papers receiving 1.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Johanna Uusimaa Finland 24 1.3k 747 194 169 154 82 1.8k
Felix Distelmaier Germany 27 1.7k 1.2× 661 0.9× 148 0.8× 52 0.3× 67 0.4× 74 2.3k
Kei Murayama Japan 23 1.3k 0.9× 829 1.1× 175 0.9× 69 0.4× 164 1.1× 169 2.0k
Manuel Schiff France 25 1.3k 1.0× 870 1.2× 255 1.3× 62 0.4× 200 1.3× 115 2.3k
Denise M. Kirby Australia 28 2.9k 2.2× 1.9k 2.6× 249 1.3× 48 0.3× 124 0.8× 45 3.4k
Sara Seneca Belgium 34 2.4k 1.8× 1.1k 1.4× 511 2.6× 55 0.3× 309 2.0× 135 3.5k
Anna Majander Finland 21 1.3k 1.0× 678 0.9× 111 0.6× 38 0.2× 45 0.3× 44 1.7k
Neal Sondheimer United States 27 2.0k 1.5× 378 0.5× 223 1.1× 26 0.2× 92 0.6× 62 2.5k
Pilar Rodríguez‐Pombo Spain 22 870 0.6× 730 1.0× 171 0.9× 28 0.2× 78 0.5× 57 1.3k
Robert D. S. Pitceathly United Kingdom 25 1.2k 0.9× 600 0.8× 124 0.6× 67 0.4× 43 0.3× 75 1.6k
Rachel Sullivan United States 3 1.3k 1.0× 337 0.5× 79 0.4× 13 0.1× 47 0.3× 4 1.7k

Countries citing papers authored by Johanna Uusimaa

Since Specialization
Citations

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

Fields of papers citing papers by Johanna Uusimaa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Johanna Uusimaa

This figure shows the co-authorship network connecting the top 25 collaborators of Johanna Uusimaa. A scholar is included among the top collaborators of Johanna Uusimaa 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 Johanna Uusimaa. Johanna Uusimaa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Huhtaniska, Sanna, Tytti Pokka, Salla M. Kangas, et al.. (2025). Phenotypic Heterogeneity in Genetic and Acquired Pediatric Cerebellar Disorders. Movement Disorders. 40(9). 1851–1862.
2.
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Uusimaa, Johanna, et al.. (2024). Wearable Motion Sensors in the Detection of ADHD: A Critical Review. Communications in computer and information science. 168–185. 2 indexed citations
4.
Kangas, Salla M., Estrella López‐Martín, Timothy Feyma, et al.. (2024). Hyperkinetic Movement Disorder Caused by the Recurrent c. 892C >T NACC1 Variant. Movement Disorders Clinical Practice. 11(6). 708–715. 1 indexed citations
5.
Kangas, Salla M., Elisa Rahikkala, Tytti Pokka, et al.. (2024). Brain MRI findings in paediatric genetic disorders associated with white matter abnormalities. Developmental Medicine & Child Neurology. 67(2). 186–194. 1 indexed citations
6.
Rahikkala, Elisa, Maria Suo‐Palosaari, Päivi Vieira, et al.. (2024). Optical Genome Mapping Identifies a Second Xq27.1 Rearrangement Associated With Charcot–Marie–Tooth Neuropathy CMTX3. Molecular Genetics & Genomic Medicine. 12(9). e70014–e70014.
7.
Kang, Yilin, Jussi Hepojoki, Takayuki Mito, et al.. (2024). Ancestral allele of DNA polymerase gamma modifies antiviral tolerance. Nature. 628(8009). 844–853. 11 indexed citations
8.
Rahikkala, Elisa, Mika Kallio, Salla M. Kangas, et al.. (2024). A novel pathogenic SLC12A5 missense variant in epilepsy of infancy with migrating focal seizures causes impaired KCC2 chloride extrusion. Frontiers in Molecular Neuroscience. 17. 1372662–1372662. 4 indexed citations
9.
Kangas, Salla M., Bishwa Ghimire, Pirkko Mattila, et al.. (2022). Analysis of human brain tissue derived from DBS surgery. Translational Neurodegeneration. 11(1). 22–22. 7 indexed citations
10.
Vissing, John, Elsebet Østergaard, Laurence A. Bindoff, et al.. (2021). Phenotypic spectrum and clinical course of single large-scale mitochondrial DNA deletion disease in the paediatric population: a multicentre study. Journal of Medical Genetics. 60(1). 65–73. 11 indexed citations
11.
Heikkinen, Anne, Salla M. Kangas, Marika Karikoski, et al.. (2021). Modeling Rare Human Disorders in Mice: The Finnish Disease Heritage. Cells. 10(11). 3158–3158. 4 indexed citations
12.
Vieira, Päivi, Elisa Rahikkala, Marja‐Leena Väisänen, et al.. (2021). Cytosolic phosphoenolpyruvate carboxykinase deficiency: Expanding the clinical phenotype and novel laboratory findings. Journal of Inherited Metabolic Disease. 45(2). 223–234. 9 indexed citations
13.
Hikmat, Omar, K Naess, Martin Engvall, et al.. (2020). The impact of gender, puberty, and pregnancy in patients with POLG disease. Annals of Clinical and Translational Neurology. 7(10). 2019–2025. 8 indexed citations
14.
Pyle, Angela, Maria Suo‐Palosaari, Jennifer Duff, et al.. (2020). Homozygous TAF1C variants are associated with a novel childhood‐onset neurological phenotype. Clinical Genetics. 98(5). 493–498. 3 indexed citations
15.
Hikmat, Omar, K Naess, Martin Engvall, et al.. (2020). Simplifying the clinical classification of polymerase gamma (POLG) disease based on age of onset; studies using a cohort of 155 cases. Journal of Inherited Metabolic Disease. 43(4). 726–736. 46 indexed citations
16.
Hikmat, Omar, K Naess, Martin Engvall, et al.. (2018). Elevated cerebrospinal fluid protein in POLG‐related epilepsy: Diagnostic and prognostic implications. Epilepsia. 59(8). 1595–1602. 6 indexed citations
17.
Biterova, Ekaterina, et al.. (2018). Structural analysis of human NHLRC2, mutations of which are associated with FINCA disease. PLoS ONE. 13(8). e0202391–e0202391. 13 indexed citations
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Sofou, Kalliopi, I.F.M. de Coo, Pirjo Isohanni, et al.. (2014). A multicenter study on Leigh syndrome: disease course and predictors of survival. Orphanet Journal of Rare Diseases. 9(1). 52–52. 161 indexed citations
20.
Remes, Anne M., Reetta Hinttala, Mikko Kärppä, et al.. (2008). Parkinsonism associated with the homozygous W748S mutation in the POLG1 gene. Parkinsonism & Related Disorders. 14(8). 652–654. 31 indexed citations

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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