Suvi Annala

739 total citations
9 papers, 211 citations indexed

About

Suvi Annala is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Biochemistry. According to data from OpenAlex, Suvi Annala has authored 9 papers receiving a total of 211 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Cellular and Molecular Neuroscience and 2 papers in Biochemistry. Recurrent topics in Suvi Annala's work include Receptor Mechanisms and Signaling (8 papers), Protein Kinase Regulation and GTPase Signaling (4 papers) and Amino Acid Enzymes and Metabolism (2 papers). Suvi Annala is often cited by papers focused on Receptor Mechanisms and Signaling (8 papers), Protein Kinase Regulation and GTPase Signaling (4 papers) and Amino Acid Enzymes and Metabolism (2 papers). Suvi Annala collaborates with scholars based in Germany, United States and Slovakia. Suvi Annala's co-authors include Evi Kostenis, Gabriele M. König, Christa E. Müller, Max Crüsemann, Raphael Reher, Stefan Kehraus, Bernd K. Fleischmann, Tobias Benkel, Daniel Tietze and Diana Imhof and has published in prestigious journals such as Journal of Biological Chemistry, Chemistry - A European Journal and Science Translational Medicine.

In The Last Decade

Suvi Annala

9 papers receiving 210 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Suvi Annala Germany	7	179	29	26	22	20	9	211
Tobias Benkel Germany	6	115 0.6×	41 1.4×	8 0.3×	5 0.2×	5 0.3×	6	170
Ilchung Shin South Korea	9	201 1.1×	53 1.8×	102 3.9×	14 0.6×	2 0.1×	12	401
Stepan Lenevich United States	8	336 1.9×	33 1.1×	14 0.5×	15 0.7×	93 4.7×	10	413
Susan D. Orwig United States	8	251 1.4×	18 0.6×	15 0.6×	7 0.3×	146 7.3×	8	335
Kota N. Gopalakrishna United States	10	227 1.3×	47 1.6×	22 0.8×	1 0.0×	28 1.4×	20	295
Tomomi Uchikubo‐Kamo Japan	11	255 1.4×	19 0.7×	29 1.1×	7 0.3×		19	334
Mathias Laga Belgium	5	174 1.0×	39 1.3×	38 1.5×	9 0.4×		6	305
Tania Tahtouh France	5	225 1.3×	10 0.3×	44 1.7×	2 0.1×	3 0.1×	8	383
Antonella Scaglione United States	10	250 1.4×	60 2.1×	27 1.0×	9 0.4×	1 0.1×	11	334
Denise Nikodemus Germany	6	129 0.7×	9 0.3×	16 0.6×	13 0.6×	1 0.1×	7	184

Countries citing papers authored by Suvi Annala

Since Specialization

Citations

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

Fields of papers citing papers by Suvi Annala

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suvi Annala

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

All Works

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9 of 9 papers shown

Nubbemeyer, Britta, Toni Kühl, Maryam A. Shetab Boushehri, et al.. (2022). Targeting Gαi/s Proteins with Peptidyl Nucleotide Exchange Modulators. ACS Chemical Biology. 17(2). 463–473. 9 indexed citations

Kostenis, Evi, et al.. (2020). Heterotrimeric Gq proteins as therapeutic targets?. Journal of Biological Chemistry. 295(16). 5206–5215. 57 indexed citations

Benkel, Tobias, Suvi Annala, Kenichi Kimura, et al.. (2020). Tetrahydroimidazo[1,2‐a]pyrazine Derivatives: Synthesis and Evaluation as Gα_q‐Protein Ligands. Chemistry - A European Journal. 26(55). 12615–12623. 6 indexed citations

Malfacini, Davide, Suvi Annala, Kasper Harpsøe, et al.. (2019). Rational design of a heterotrimeric G protein α subunit with artificial inhibitor sensitivity. Journal of Biological Chemistry. 294(15). 5747–5758. 25 indexed citations

Benkel, Tobias, et al.. (2019). BIM-46174 fragments as potential ligands of G proteins. MedChemComm. 10(10). 1838–1843. 5 indexed citations

Reher, Raphael, Toni Kühl, Suvi Annala, et al.. (2018). Deciphering Specificity Determinants for FR900359‐Derived G_qα Inhibitors Based on Computational and Structure–Activity Studies. ChemMedChem. 13(16). 1634–1643. 31 indexed citations

Reher, Raphael, Nina Heycke, Suvi Annala, et al.. (2018). Applying Molecular Networking for the Detection of Natural Sources and Analogues of the Selective Gq Protein Inhibitor FR900359. Journal of Natural Products. 81(7). 1628–1635. 26 indexed citations

Matthey, Michaela, Richard Roberts, Annika Simon, et al.. (2017). Targeted inhibition of G_qsignaling induces airway relaxation in mouse models of asthma. Science Translational Medicine. 9(407). 44 indexed citations

Leiss, Veronika, Suvi Annala, Jochen Müller‐Ehmsen, et al.. (2015). Lack of Gα_i2leads to dilative cardiomyopathy and increased mortality in β₁-adrenoceptor overexpressing mice. Cardiovascular Research. 108(3). 348–356. 8 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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