Martin Laasmaa

678 total citations
30 papers, 340 citations indexed

About

Martin Laasmaa is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Biophysics. According to data from OpenAlex, Martin Laasmaa has authored 30 papers receiving a total of 340 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Cardiology and Cardiovascular Medicine, 12 papers in Molecular Biology and 9 papers in Biophysics. Recurrent topics in Martin Laasmaa's work include Cardiac electrophysiology and arrhythmias (16 papers), Ion channel regulation and function (9 papers) and Advanced Fluorescence Microscopy Techniques (6 papers). Martin Laasmaa is often cited by papers focused on Cardiac electrophysiology and arrhythmias (16 papers), Ion channel regulation and function (9 papers) and Advanced Fluorescence Microscopy Techniques (6 papers). Martin Laasmaa collaborates with scholars based in Estonia, Norway and United Kingdom. Martin Laasmaa's co-authors include Marko Vendelin, Pearu Peterson, Rikke Birkedal, William E. Louch, Ivar Sjaastad, Ornella Manfra, Jüri Engelbrecht, Tanel Peets, Andrew G. Edwards and Kert Tamm and has published in prestigious journals such as Circulation Research, The Journal of Physiology and Scientific Reports.

In The Last Decade

Martin Laasmaa

27 papers receiving 336 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Martin Laasmaa Estonia 11 148 124 62 53 40 30 340
Alexander Vallmitjana United States 11 250 1.7× 156 1.3× 47 0.8× 86 1.6× 52 1.3× 28 357
Armen R. Kherlopian United States 6 149 1.0× 107 0.9× 101 1.6× 38 0.7× 47 1.2× 8 378
Yunfei Huang China 11 119 0.8× 76 0.6× 65 1.0× 10 0.2× 67 1.7× 47 487
Joe B. Hakim United States 11 151 1.0× 397 3.2× 42 0.7× 12 0.2× 23 0.6× 14 655
A. Sarkar United States 8 178 1.2× 49 0.4× 124 2.0× 40 0.8× 64 1.6× 10 471
V. Nikolski United States 9 206 1.4× 332 2.7× 87 1.4× 45 0.8× 117 2.9× 12 514
Seung Yup Lee United States 13 193 1.3× 20 0.2× 130 2.1× 52 1.0× 22 0.6× 49 501
Veniamin Y. Sidorov United States 13 274 1.9× 438 3.5× 147 2.4× 21 0.4× 156 3.9× 30 743
June Hoan Kim South Korea 10 113 0.8× 22 0.2× 72 1.2× 53 1.0× 53 1.3× 18 302
Michael A. Colman United Kingdom 17 257 1.7× 766 6.2× 24 0.4× 26 0.5× 105 2.6× 51 871

Countries citing papers authored by Martin Laasmaa

Since Specialization
Citations

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

Fields of papers citing papers by Martin Laasmaa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Laasmaa

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Laasmaa. A scholar is included among the top collaborators of Martin Laasmaa 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 Martin Laasmaa. Martin Laasmaa 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.
Birkedal, Rikke, et al.. (2023). Simple analysis of gel images with IOCBIO Gel. BMC Biology. 21(1). 225–225. 5 indexed citations
2.
Li, Jia, Joakim Sundnes, Yufeng Hou, et al.. (2023). Stretch Harmonizes Sarcomere Strain Across the Cardiomyocyte. Circulation Research. 133(3). 255–270. 11 indexed citations
3.
Laasmaa, Martin, et al.. (2023). Cardiomyocytes from female compared to male mice have larger ryanodine receptor clusters and higher calcium spark frequency. The Journal of Physiology. 601(18). 4033–4052. 6 indexed citations
4.
Shen, Xin, Terje R. Kolstad, Einar Sjaastad Nordén, et al.. (2022). Prolonged β-adrenergic stimulation disperses ryanodine receptor clusters in cardiomyocytes and has implications for heart failure. eLife. 11. 17 indexed citations
5.
Vendelin, Marko, et al.. (2020). IOCBIO Kinetics: An open-source software solution for analysis of data traces. PLoS Computational Biology. 16(12). e1008475–e1008475. 3 indexed citations
6.
Hou, Yufeng, Martin Laasmaa, Jia Li, et al.. (2020). Correlating Calcium Sparks and Ryanodine Receptor Localization in Live Cardiomyocytes. Biophysical Journal. 118(3). 567a–567a. 1 indexed citations
7.
Frisk, Michael, Martin Laasmaa, Alexandre Lewalle, et al.. (2020). Hypokalemia Promotes Arrhythmia by Distinct Mechanisms in Atrial and Ventricular Myocytes. Biophysical Journal. 118(3). 103a–103a. 2 indexed citations
8.
Rubinstein, Jack, Jessica G. Woo, Anastacia M. Garcia, et al.. (2020). Probenecid Improves Cardiac Function in Subjects with a Fontan Circulation and Augments Cardiomyocyte Calcium Homeostasis. Pediatric Cardiology. 41(8). 1675–1688. 13 indexed citations
9.
Laasmaa, Martin, et al.. (2019). Iocbio Sparks Detection and Analysis Software. Biophysical Journal. 116(3). 384a–384a.
10.
Laasmaa, Martin, et al.. (2019). Respiration of permeabilized cardiomyocytes from mice: no sex differences, but substrate-dependent changes in the apparent ADP-affinity. Scientific Reports. 9(1). 12592–12592. 5 indexed citations
11.
Laasmaa, Martin, et al.. (2019). IOCBIO Sparks detection and analysis software. PeerJ. 7. e6652–e6652. 9 indexed citations
12.
Laasmaa, Martin, et al.. (2016). Metabolic compartmentation in rainbow trout cardiomyocytes: coupling of hexokinase but not creatine kinase to mitochondrial respiration. Journal of Comparative Physiology B. 187(1). 103–116. 6 indexed citations
13.
Laasmaa, Martin, et al.. (2016). Restricted ADP movement in cardiomyocytes: Cytosolic diffusion obstacles are complemented with a small number of open mitochondrial voltage-dependent anion channels. Journal of Molecular and Cellular Cardiology. 97. 197–203. 26 indexed citations
14.
Laasmaa, Martin, Rikke Birkedal, & Marko Vendelin. (2016). Revealing calcium fluxes by analyzing inhibition dynamics in action potential clamp. Journal of Molecular and Cellular Cardiology. 100. 93–108. 5 indexed citations
15.
Birkedal, Rikke, Martin Laasmaa, & Marko Vendelin. (2014). The location of energetic compartments affects energetic communication in cardiomyocytes. Frontiers in Physiology. 5. 376–376. 15 indexed citations
16.
Laasmaa, Martin, et al.. (2012). Analysis of Molecular Movement Reveals Latticelike Obstructions to Diffusion in Heart Muscle Cells. Biophysical Journal. 102(4). 739–748. 28 indexed citations
17.
Laasmaa, Martin, Marko Vendelin, & Pearu Peterson. (2011). Application of regularized Richardson-Lucy algorithm for deconvolution of confocal microscopy images. Journal of Microscopy. 243(2). 124–140. 73 indexed citations
18.
Laasmaa, Martin, Marko Vendelin, & Pearu Peterson. (2011). Application of Regularized Richardson-Lucy Algorithm for Deconvolution of Confocal Microscopy Images. Biophysical Journal. 100(3). 139a–139a. 6 indexed citations
19.
Laasmaa, Martin, Marko Vendelin, & Pearu Peterson. (2010). 3D Confocal Microscope Image Enhancement by Richardson-Lucy Deconvolution Algorithm with Total Variation Regularization: Parameters Estimation. Biophysical Journal. 98(3). 178a–178a. 1 indexed citations
20.
Laasmaa, Martin, et al.. (2010). Determination of Regional Diffusion Coefficients of Fluorescent ATP in Rat Cardiomyocytes. Biophysical Journal. 98(3). 749a–749a. 1 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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