Ian R. Lanza
- Physiology top 0.5%
- Molecular Biology top 2%
- Cell Biology top 1%
- Epidemiology top 5%
- Complementary and alternative medicine top 0.5%
- Co-authors
- K. Sreekumaran NairJane A. Kent‐BraunSurendra DasariMatthew L. JohnsonMatthew M. RobinsonAntigoni Z. LaliaDavid W. RussBrian A. Irving
- Topics
- Adipose Tissue and Metabolism (47 papers)Muscle metabolism and nutrition (24 papers)Mitochondrial Function and Pathology (23 papers)
- Partner nations
- United StatesChinaItaly
In The Last Decade
Ian R. Lanza
109 papers receiving 6.3k citations
Hit Papers
Peers
Comparison fields: 5 of 145
- Physiology 3.2k
- Molecular Biology 2.8k
- Cell Biology 1.0k
- Epidemiology 733
- Complementary and alternative medicine 676
Countries citing papers authored by Ian R. Lanza
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
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
| # | 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 Humansbreakdown → | 377 |
| 15 | 30 | |
| 16 | 212 | |
| 17 | A PGC-1α Isoform Induced by Resistance Training Regulates Skeletal Muscle Hypertrophybreakdown → | 531 |
| 18 | 48 | |
| 19 | 9 | |
| 20 | 76 |
About Ian R. Lanza
Ian R. Lanza is a scholar working on Aging, Physiology and Complementary and alternative medicine, having authored 112 papers that have together received 6.4k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (47 papers), Muscle metabolism and nutrition (24 papers) and Mitochondrial Function and Pathology (23 papers). The work is most often cited by research in Physiology (3.2k citations), Aging (184 citations) and Complementary and alternative medicine (676 citations). Ian R. Lanza has collaborated with scholars based in United States, China and Italy. Frequent 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. Their work appears in journals such as Cell, Journal of Biological Chemistry and Nature Communications.
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.