Ian R. Lanza

10.8k total citations · 2 hit papers
112 papers, 6.4k citations indexed

About

Ian R. Lanza is a scholar working on Physiology, Molecular Biology and Cell Biology. According to data from OpenAlex, Ian R. Lanza has authored 112 papers receiving a total of 6.4k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Physiology, 58 papers in Molecular Biology and 24 papers in Cell Biology. Recurrent topics in Ian R. Lanza's work include Adipose Tissue and Metabolism (47 papers), Muscle metabolism and nutrition (24 papers) and Mitochondrial Function and Pathology (23 papers). Ian R. Lanza is often cited by papers focused on Adipose Tissue and Metabolism (47 papers), Muscle metabolism and nutrition (24 papers) and Mitochondrial Function and Pathology (23 papers). Ian R. Lanza collaborates with scholars based in United States, China and Italy. Ian R. Lanza's co-authors include K. Sreekumaran Nair, Jane A. Kent‐Braun, Surendra Dasari, Matthew L. Johnson, Matthew M. Robinson, Antigoni Z. Lalia, David W. Russ, Brian A. Irving, Douglas E. Befroy and Adam R. Konopka and has published in prestigious journals such as Cell, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Ian R. Lanza

109 papers receiving 6.3k citations

Hit Papers

A PGC-1α Isoform Induced by Resistance Training Regulates... 2012 2026 2016 2021 2012 2017 100 200 300 400 500

Peers

Ian R. Lanza
Comparison fields: 5 of 145
  • Physiology 3.2k
  • Molecular Biology 2.8k
  • Cell Biology 1.0k
  • Epidemiology 733
  • Complementary and alternative medicine 676
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Citations per field, relative to Ian R. Lanza
Ian R. Lanza · 1×
Citations per year, relative to Ian R. Lanza
Ian R. Lanza · 1×

Countries citing papers authored by Ian R. Lanza

Since Specialization
Citations

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

Fields of papers citing papers by Ian R. Lanza

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ian R. Lanza

This figure shows the co-authorship network connecting the top 25 collaborators of Ian R. Lanza. A scholar is included among the top collaborators of Ian R. Lanza 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 Ian R. Lanza. Ian R. Lanza 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
# Work Indexed citations
1 1
2 7
3 0
4 2
5 1
6 9
7 50
8 12
9 127
10 15
11 36
12 2
13 9
14
Enhanced Protein Translation Underlies Improved Metabolic and Physical Adaptations to Different Exercise Training Modes in Young and Old Humans breakdown →
377
15 30
16 212
17
A PGC-1α Isoform Induced by Resistance Training Regulates Skeletal Muscle Hypertrophy breakdown →
531
18 48
19 9
20 76

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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