Aigar Ottas

566 total citations
18 papers, 413 citations indexed

About

Aigar Ottas is a scholar working on Molecular Biology, Dermatology and Physiology. According to data from OpenAlex, Aigar Ottas has authored 18 papers receiving a total of 413 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 5 papers in Dermatology and 5 papers in Physiology. Recurrent topics in Aigar Ottas's work include Metabolomics and Mass Spectrometry Studies (5 papers), Dermatology and Skin Diseases (4 papers) and Tryptophan and brain disorders (3 papers). Aigar Ottas is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (5 papers), Dermatology and Skin Diseases (4 papers) and Tryptophan and brain disorders (3 papers). Aigar Ottas collaborates with scholars based in Estonia and Sweden. Aigar Ottas's co-authors include Ursel Soomets, Mihkel Zilmer, Külli Kingo, Jaak Kals, Kaido Paapstel, Kaspar Tootsi, Dmytro Fishman, Jaan Eha, J. Lieberg and Kalle Kilk and has published in prestigious journals such as PLoS ONE, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Aigar Ottas

18 papers receiving 409 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aigar Ottas Estonia 10 193 98 77 70 55 18 413
Michael Siegel United States 11 293 1.5× 161 1.6× 106 1.4× 58 0.8× 9 0.2× 21 545
Gülcan Güntaş Türkiye 13 60 0.3× 98 1.0× 52 0.7× 17 0.2× 51 0.9× 25 372
Andrea Crucitti Italy 4 97 0.5× 88 0.9× 89 1.2× 13 0.2× 10 0.2× 6 346
Maja Stojković Serbia 11 88 0.5× 86 0.9× 36 0.5× 69 1.0× 23 0.4× 16 393
Paula K. Bautista‐Niño Colombia 10 127 0.7× 111 1.1× 47 0.6× 16 0.2× 19 0.3× 28 431
Yukiko Todoroki Japan 10 108 0.6× 93 0.9× 60 0.8× 79 1.1× 23 0.4× 14 470
Sitao Li China 12 158 0.8× 51 0.5× 83 1.1× 7 0.1× 103 1.9× 44 469
Yaguang Hu China 12 155 0.8× 42 0.4× 31 0.4× 16 0.2× 22 0.4× 33 466
Marina P. Catalán Spain 14 141 0.7× 37 0.4× 79 1.0× 5 0.1× 50 0.9× 17 502
Sama Bitarafan Iran 15 194 1.0× 70 0.7× 124 1.6× 14 0.2× 9 0.2× 41 638

Countries citing papers authored by Aigar Ottas

Since Specialization
Citations

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

Fields of papers citing papers by Aigar Ottas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aigar Ottas

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

All Works

18 of 18 papers shown
1.
Traks, Tanel, Paula Reemann, Kattri‐Liis Eskla, et al.. (2024). High‐throughput proteomic analysis of chronic inflammatory skin diseases: Psoriasis and atopic dermatitis. Experimental Dermatology. 33(4). e15079–e15079. 3 indexed citations
2.
Ottas, Aigar, et al.. (2023). Changes in Lipoprotein Particles in the Blood Serum of Patients with Lichen Planus. Metabolites. 13(1). 91–91. 3 indexed citations
3.
Ottas, Aigar, et al.. (2022). Apnoea–hypopnoea index of 5 events·h−1as a metabolomic threshold in patients with sleep complaints. ERJ Open Research. 9(1). 325–2022. 1 indexed citations
4.
Ottas, Aigar, Kristi Abram, Ursel Soomets, et al.. (2022). Metabolomic Differences between the Skin and Blood Sera of Atopic Dermatitis and Psoriasis. International Journal of Molecular Sciences. 23(21). 13001–13001. 8 indexed citations
5.
Lieberg, J., Anders Wanhainen, Aigar Ottas, et al.. (2021). Metabolomic Profile of Abdominal Aortic Aneurysm. Metabolites. 11(8). 555–555. 14 indexed citations
6.
Ottas, Aigar, et al.. (2021). The effect of obstructive sleep apnea on peripheral blood amino acid and biogenic amine metabolome at multiple time points overnight. Scientific Reports. 11(1). 10811–10811. 9 indexed citations
7.
Soeorg, Hiie, et al.. (2021). Seroprevalence and levels of IgG antibodies after COVID-19 infection or vaccination. Infectious Diseases. 54(1). 63–71. 15 indexed citations
8.
Ottas, Aigar, Kristi Abram, Ursel Soomets, et al.. (2020). Hyperproliferation is the main driver of metabolomic changes in psoriasis lesional skin. Scientific Reports. 10(1). 3081–3081. 42 indexed citations
9.
Innos, Jürgen, Mari‐Anne Philips, Aigar Ottas, et al.. (2018). Repeated Administration of D-Amphetamine Induces Distinct Alterations in Behavior and Metabolite Levels in 129Sv and Bl6 Mouse Strains. Frontiers in Neuroscience. 12. 399–399. 9 indexed citations
10.
Innos, Jürgen, Mari‐Anne Philips, Aigar Ottas, et al.. (2018). Metabolic profile associated with distinct behavioral coping strategies of 129Sv and Bl6 mice in repeated motility test. Scientific Reports. 8(1). 3405–3405. 9 indexed citations
11.
Kilk, Kalle, et al.. (2018). Phenotyping of Chronic Obstructive Pulmonary Disease Based on the Integration of Metabolomes and Clinical Characteristics. International Journal of Molecular Sciences. 19(3). 666–666. 46 indexed citations
12.
Tootsi, Kaspar, Jaak Kals, Mihkel Zilmer, et al.. (2018). Medium‐ and long‐chain acylcarnitines are associated with osteoarthritis severity and arterial stiffness in end‐stage osteoarthritis patients: a case‐control study. International Journal of Rheumatic Diseases. 21(6). 1211–1218. 24 indexed citations
13.
Ottas, Aigar, Dmytro Fishman, Tõnu Püssa, et al.. (2017). Blood serum metabolome of atopic dermatitis: Altered energy cycle and the markers of systemic inflammation. PLoS ONE. 12(11). e0188580–e0188580. 34 indexed citations
14.
Ottas, Aigar, et al.. (2017). The metabolic analysis of psoriasis identifies the associated metabolites while providing computational models for the monitoring of the disease. Archives of Dermatological Research. 309(7). 519–528. 51 indexed citations
15.
Paapstel, Kaido, Jaak Kals, Jaan Eha, et al.. (2017). Inverse relations of serum phosphatidylcholines and lysophosphatidylcholines with vascular damage and heart rate in patients with atherosclerosis. Nutrition Metabolism and Cardiovascular Diseases. 28(1). 44–52. 83 indexed citations
16.
Ottas, Aigar, Ursel Soomets, Kati Koido, et al.. (2017). Profiling of Acylcarnitines in First Episode Psychosis before and after Antipsychotic Treatment. Journal of Proteome Research. 16(10). 3558–3566. 36 indexed citations
17.
Koido, Kati, Jürgen Innos, Liina Haring, et al.. (2016). Taurine and Epidermal Growth Factor Belong to the Signature of First-Episode Psychosis. Frontiers in Neuroscience. 10. 331–331. 9 indexed citations
18.
Paapstel, Kaido, Jaak Kals, Jaan Eha, et al.. (2016). Metabolomic profiles of lipid metabolism, arterial stiffness and hemodynamics in male coronary artery disease patients. 11. 13–18. 17 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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