Matthew R. Locher

501 total citations
7 papers, 403 citations indexed

About

Matthew R. Locher is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Surgery. According to data from OpenAlex, Matthew R. Locher has authored 7 papers receiving a total of 403 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cardiology and Cardiovascular Medicine, 4 papers in Molecular Biology and 1 paper in Surgery. Recurrent topics in Matthew R. Locher's work include Cardiomyopathy and Myosin Studies (5 papers), Cardiovascular Effects of Exercise (5 papers) and Muscle Physiology and Disorders (3 papers). Matthew R. Locher is often cited by papers focused on Cardiomyopathy and Myosin Studies (5 papers), Cardiovascular Effects of Exercise (5 papers) and Muscle Physiology and Disorders (3 papers). Matthew R. Locher collaborates with scholars based in United States and Sweden. Matthew R. Locher's co-authors include Richard L. Moss, Brett A. Colson, Thomas C. Irving, Daniel P. Fitzsimons, Tanya Bekyarova, Julian E. Stelzer, Jitandrakumar R. Patel, Stacey Brickson, Holly S. Norman and Maria V. Razumova and has published in prestigious journals such as Circulation Research, Analytical Chemistry and The Journal of Physiology.

In The Last Decade

Matthew R. Locher

7 papers receiving 400 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew R. Locher United States 7 318 227 39 27 22 7 403
Lisa Martin United States 8 396 1.2× 276 1.2× 14 0.4× 14 0.5× 19 0.9× 9 478
Eileen M. Burkart United States 7 367 1.2× 357 1.6× 31 0.8× 14 0.5× 24 1.1× 7 550
Xin Shen Norway 10 191 0.6× 147 0.6× 30 0.8× 6 0.2× 20 0.9× 36 288
Cheavar A. Blair United States 10 236 0.7× 141 0.6× 43 1.1× 4 0.1× 22 1.0× 17 322
Aref Najafi Netherlands 11 479 1.5× 246 1.1× 51 1.3× 3 0.1× 21 1.0× 14 580
Judith Krysiak Germany 5 305 1.0× 158 0.7× 18 0.5× 4 0.1× 20 0.9× 6 345
Khiem Nguyen United States 11 159 0.5× 132 0.6× 82 2.1× 10 0.4× 19 0.9× 19 433
R J Solaro United States 10 316 1.0× 211 0.9× 15 0.4× 5 0.2× 23 1.0× 15 401
Zengyi Chen United States 12 303 1.0× 131 0.6× 28 0.7× 3 0.1× 13 0.6× 18 405
Joachim Günther Germany 9 253 0.8× 171 0.8× 30 0.8× 5 0.2× 17 0.8× 16 417

Countries citing papers authored by Matthew R. Locher

Since Specialization
Citations

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

Fields of papers citing papers by Matthew R. Locher

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew R. Locher. 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 Matthew R. Locher. The network helps show where Matthew R. Locher may publish in the future.

Co-authorship network of co-authors of Matthew R. Locher

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

All Works

7 of 7 papers shown
1.
Chen, Yi‐Chen, Şerife Ayaz‐Güner, Ying Peng, et al.. (2015). Effective Top-Down LC/MS+ Method for Assessing Actin Isoforms as a Potential Cardiac Disease Marker. Analytical Chemistry. 87(16). 8399–8406. 25 indexed citations
2.
Osaki, Satoru, Matthew R. Locher, Entela B. Lushaj, Shahab A. Akhter, & Takushi Kohmoto. (2014). Functional evaluation of human donation after cardiac death donor hearts using a continuous isolated myocardial perfusion technique: Potential for expansion of the cardiac donor population. Journal of Thoracic and Cardiovascular Surgery. 148(3). 1123–1130. 18 indexed citations
3.
Locher, Matthew R., Maria V. Razumova, Julian E. Stelzer, Holly S. Norman, & Richard L. Moss. (2011). Effects of low-level α-myosin heavy chain expression on contractile kinetics in porcine myocardium. American Journal of Physiology-Heart and Circulatory Physiology. 300(3). H869–H878. 36 indexed citations
4.
Colson, Brett A., Matthew R. Locher, Tanya Bekyarova, et al.. (2010). Differential roles of regulatory light chain and myosin binding protein-C phosphorylations in the modulation of cardiac force development. The Journal of Physiology. 588(6). 981–993. 142 indexed citations
5.
Locher, Matthew R., Maria V. Razumova, Julian E. Stelzer, et al.. (2009). Determination of rate constants for turnover of myosin isoforms in rat myocardium: implications for in vivo contractile kinetics. American Journal of Physiology-Heart and Circulatory Physiology. 297(1). H247–H256. 31 indexed citations
6.
Colson, Brett A., Tanya Bekyarova, Matthew R. Locher, et al.. (2008). Protein Kinase A–Mediated Phosphorylation of cMyBP-C Increases Proximity of Myosin Heads to Actin in Resting Myocardium. Circulation Research. 103(3). 244–251. 97 indexed citations
7.
Stelzer, Julian E., Stacey Brickson, Matthew R. Locher, & Richard L. Moss. (2006). Role of myosin heavy chain composition in the stretch activation response of rat myocardium. The Journal of Physiology. 579(1). 161–173. 54 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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