Gordon J. Lutz

2.0k total citations
30 papers, 1.6k citations indexed

About

Gordon J. Lutz is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Biomedical Engineering. According to data from OpenAlex, Gordon J. Lutz has authored 30 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 13 papers in Cardiology and Cardiovascular Medicine and 9 papers in Biomedical Engineering. Recurrent topics in Gordon J. Lutz's work include Muscle Physiology and Disorders (20 papers), Cardiomyopathy and Myosin Studies (13 papers) and RNA Interference and Gene Delivery (9 papers). Gordon J. Lutz is often cited by papers focused on Muscle Physiology and Disorders (20 papers), Cardiomyopathy and Myosin Studies (13 papers) and RNA Interference and Gene Delivery (9 papers). Gordon J. Lutz collaborates with scholars based in United States, Sweden and Switzerland. Gordon J. Lutz's co-authors include Lawrence C. Rome, Shashank R. Sirsi, Richard L. Lieber, Jason H. Williams, Frank T. Scott, R. McNeill Alexander, Roel Funke, Martin Glodde, A. Sosnicki and Jan Fridén and has published in prestigious journals such as Nature, Science and Journal of Neuroscience.

In The Last Decade

Gordon J. Lutz

30 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gordon J. Lutz United States 22 776 493 242 239 222 30 1.6k
N. A. Curtin United Kingdom 29 955 1.2× 1.3k 2.6× 300 1.2× 1.1k 4.8× 365 1.6× 80 2.5k
Benjamin W. C. Rosser Canada 19 599 0.8× 93 0.2× 245 1.0× 120 0.5× 73 0.3× 43 1.2k
Douglas A. Syme Canada 20 248 0.3× 333 0.7× 465 1.9× 238 1.0× 157 0.7× 49 1.3k
Robert S. Hikida United States 25 824 1.1× 562 1.1× 178 0.7× 267 1.1× 945 4.3× 60 2.6k
Frederick J. Samaha United States 21 1.6k 2.1× 491 1.0× 144 0.6× 438 1.8× 162 0.7× 47 2.8k
Nicholas J. Cole Australia 30 1.2k 1.5× 91 0.2× 290 1.2× 114 0.5× 20 0.1× 64 2.3k
Jenna A. Monroy United States 15 205 0.3× 282 0.6× 73 0.3× 234 1.0× 85 0.4× 23 658
S. R. Young United Kingdom 26 385 0.5× 347 0.7× 466 1.9× 19 0.1× 204 0.9× 45 2.2k
Scott Medler United States 16 408 0.5× 84 0.2× 138 0.6× 91 0.4× 45 0.2× 35 796
Darrell R. Stokes United States 15 145 0.2× 226 0.5× 135 0.6× 181 0.8× 81 0.4× 27 736

Countries citing papers authored by Gordon J. Lutz

Since Specialization
Citations

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

Fields of papers citing papers by Gordon J. Lutz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gordon J. Lutz. 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 Gordon J. Lutz. The network helps show where Gordon J. Lutz may publish in the future.

Co-authorship network of co-authors of Gordon J. Lutz

This figure shows the co-authorship network connecting the top 25 collaborators of Gordon J. Lutz. A scholar is included among the top collaborators of Gordon J. Lutz 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 Gordon J. Lutz. Gordon J. Lutz 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.
Lutz, Gordon J., et al.. (2017). AMPA GluA1-flip targeted oligonucleotide therapy reduces neonatal seizures and hyperexcitability. PLoS ONE. 12(2). e0171538–e0171538. 7 indexed citations
2.
Greif, Karen F., Nana Yaw Asabere, Gordon J. Lutz, & Gianluca Gallo. (2012). Synaptotagmin‐1 promotes the formation of axonal filopodia and branches along the developing axons of forebrain neurons. Developmental Neurobiology. 73(1). 27–44. 23 indexed citations
3.
Williams, Jim, et al.. (2009). Oligonucleotide-Mediated Survival of Motor Neuron Protein Expression in CNS Improves Phenotype in a Mouse Model of Spinal Muscular Atrophy. Journal of Neuroscience. 29(24). 7633–7638. 111 indexed citations
4.
Lutz, Gordon J., Shashank R. Sirsi, & Jason H. Williams. (2008). PEG–PEI Copolymers for Oligonucleotide Delivery to Cells and Tissues. Methods in molecular biology. 433. 141–150. 21 indexed citations
5.
Kim, Young-Hoon, Manorama Tewari, J. David Pajerowski, et al.. (2008). Polymersome delivery of siRNA and antisense oligonucleotides. Journal of Controlled Release. 134(2). 132–140. 134 indexed citations
6.
Kim, Young-Hoon, Manu Tewari, Shamik Sen, et al.. (2006). Efficient Nuclear Delivery and Nuclear Body Localization of Antisense Oligo-Nucleotides using Degradable Polymersomes. PubMed. 2006. 4350–4353. 6 indexed citations
7.
8.
Patel, Tina, et al.. (2004). Sarcomere strain and heterogeneity correlate with injury to frog skeletal muscle fiber bundles. Journal of Applied Physiology. 97(5). 1803–1813. 39 indexed citations
9.
Bremner, Shannon N., et al.. (2004). In vivo expression of myosin essential light chain using plasmid expression vectors in regenerating frog skeletal muscle. Gene Therapy. 12(4). 347–357. 4 indexed citations
10.
Lutz, Gordon J. & Richard L. Lieber. (2002). Studies of Myosin Isoforms in Muscle Cells: Single Cell Mechanics and Gene Transfer. Clinical Orthopaedics and Related Research. 403(403 Suppl). S51–S58. 4 indexed citations
11.
Lutz, Gordon J., et al.. (2001). Identification of myosin light chains in Rana pipiens skeletal muscle and their expression patterns along single fibres. Journal of Experimental Biology. 204(24). 4237–4248. 23 indexed citations
12.
Lutz, Gordon J. & Richard L. Lieber. (2000). Myosin isoforms in anuran skeletal muscle: Their influence on contractile properties and in vivo muscle function. Microscopy Research and Technique. 50(6). 443–457. 24 indexed citations
13.
14.
Lutz, Gordon J. & Richard L. Lieber. (1999). 3 Skeletal Muscle Myosin II Structure and Function. Exercise and Sport Sciences Reviews. 27. 63???78–63???78. 8 indexed citations
15.
Lutz, Gordon J., et al.. (1998). Quantitative analysis of muscle fibre type and myosin heavy chain Distribution in the frog hindlimb: implications for locomotory design. Journal of Muscle Research and Cell Motility. 19(7). 717–731. 41 indexed citations
16.
Lutz, Gordon J., et al.. (1998). Four novel myosin heavy chain transcripts define a molecular basis for muscle fibre types in Ranapipiens. The Journal of Physiology. 508(3). 667–680. 44 indexed citations
17.
Lutz, Gordon J., Allen F. Ryan, & Richard L. Lieber. (1997). Novel myosin heavy chain clones correlated with fiber type from skeletal muscle of Rana Pipiens. The FASEB Journal. 11(3). 1 indexed citations
18.
Lutz, Gordon J. & Lawrence C. Rome. (1996). Muscle function during jumping in frogs. I. Sarcomere length change, EMG pattern, and jumping performance. American Journal of Physiology-Cell Physiology. 271(2). C563–C570. 56 indexed citations
19.
Sosnicki, A., Gordon J. Lutz, Lawrence C. Rome, & Dallas O. Goble. (1989). Histochemical and molecular determination of fiber types in chemically skinned single equine skeletal muscle fibers.. Journal of Histochemistry & Cytochemistry. 37(11). 1731–1738. 20 indexed citations
20.
Rome, Lawrence C., et al.. (1988). Why animals have different muscle fibre types. Nature. 335(6193). 824–827. 318 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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